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/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Eric Wieser
-/
import Mathlib.Algebra.Group.Fin.Tuple
import Mathlib.Data.Matrix.RowCol
import Mathlib.Data.Fin.VecNotation
import Mathlib.Tactic.FinCases
import Mathlib.Algebra.BigOperators.Fin
/-!
# Matrix and vector notation
This file includes `simp` lemmas for applying operations in `Data.Matrix.Basic` to values built out
of the matrix notation `![a, b] = vecCons a (vecCons b vecEmpty)` defined in
`Data.Fin.VecNotation`.
This also provides the new notation `!![a, b; c, d] = Matrix.of ![![a, b], ![c, d]]`.
This notation also works for empty matrices; `!![,,,] : Matrix (Fin 0) (Fin 3)` and
`!![;;;] : Matrix (Fin 3) (Fin 0)`.
## Implementation notes
The `simp` lemmas require that one of the arguments is of the form `vecCons _ _`.
This ensures `simp` works with entries only when (some) entries are already given.
In other words, this notation will only appear in the output of `simp` if it
already appears in the input.
## Notations
This file provide notation `!![a, b; c, d]` for matrices, which corresponds to
`Matrix.of ![![a, b], ![c, d]]`.
## Examples
Examples of usage can be found in the `MathlibTest/matrix.lean` file.
-/
namespace Matrix
universe u uₘ uₙ uₒ
variable {α : Type u} {o n m : ℕ} {m' : Type uₘ} {n' : Type uₙ} {o' : Type uₒ}
open Matrix
section toExpr
open Lean Qq
open Qq in
/-- `Matrix.mkLiteralQ !![a, b; c, d]` produces the term `q(!![$a, $b; $c, $d])`. -/
def mkLiteralQ {u : Level} {α : Q(Type u)} {m n : Nat} (elems : Matrix (Fin m) (Fin n) Q($α)) :
Q(Matrix (Fin $m) (Fin $n) $α) :=
let elems := PiFin.mkLiteralQ (α := q(Fin $n → $α)) fun i => PiFin.mkLiteralQ fun j => elems i j
q(Matrix.of $elems)
/-- Matrices can be reflected whenever their entries can. We insert a `Matrix.of` to
prevent immediate decay to a function. -/
protected instance toExpr [ToLevel.{u}] [ToLevel.{uₘ}] [ToLevel.{uₙ}]
[Lean.ToExpr α] [Lean.ToExpr m'] [Lean.ToExpr n'] [Lean.ToExpr (m' → n' → α)] :
Lean.ToExpr (Matrix m' n' α) :=
have eα : Q(Type $(toLevel.{u})) := toTypeExpr α
have em' : Q(Type $(toLevel.{uₘ})) := toTypeExpr m'
have en' : Q(Type $(toLevel.{uₙ})) := toTypeExpr n'
{ toTypeExpr :=
q(Matrix $eα $em' $en')
toExpr := fun M =>
have eM : Q($em' → $en' → $eα) := toExpr (show m' → n' → α from M)
q(Matrix.of $eM) }
end toExpr
section Parser
open Lean Meta Elab Term Macro TSyntax PrettyPrinter.Delaborator SubExpr
/-- Notation for m×n matrices, aka `Matrix (Fin m) (Fin n) α`.
For instance:
* `!![a, b, c; d, e, f]` is the matrix with two rows and three columns, of type
`Matrix (Fin 2) (Fin 3) α`
* `!![a, b, c]` is a row vector of type `Matrix (Fin 1) (Fin 3) α` (see also `Matrix.row`).
* `!![a; b; c]` is a column vector of type `Matrix (Fin 3) (Fin 1) α` (see also `Matrix.col`).
This notation implements some special cases:
* `![,,]`, with `n` `,`s, is a term of type `Matrix (Fin 0) (Fin n) α`
* `![;;]`, with `m` `;`s, is a term of type `Matrix (Fin m) (Fin 0) α`
* `![]` is the 0×0 matrix
Note that vector notation is provided elsewhere (by `Matrix.vecNotation`) as `![a, b, c]`.
Under the hood, `!![a, b, c; d, e, f]` is syntax for `Matrix.of ![![a, b, c], ![d, e, f]]`.
-/
syntax (name := matrixNotation)
"!![" ppRealGroup(sepBy1(ppGroup(term,+,?), ";", "; ", allowTrailingSep)) "]" : term
@[inherit_doc matrixNotation]
syntax (name := matrixNotationRx0) "!![" ";"+ "]" : term
@[inherit_doc matrixNotation]
syntax (name := matrixNotation0xC) "!![" ","* "]" : term
macro_rules
| `(!![$[$[$rows],*];*]) => do
let m := rows.size
let n := if h : 0 < m then rows[0].size else 0
let rowVecs ← rows.mapM fun row : Array Term => do
unless row.size = n do
Macro.throwErrorAt (mkNullNode row) s!"\
Rows must be of equal length; this row has {row.size} items, \
the previous rows have {n}"
`(![$row,*])
`(@Matrix.of (Fin $(quote m)) (Fin $(quote n)) _ ![$rowVecs,*])
| `(!![$[;%$semicolons]*]) => do
let emptyVec ← `(![])
let emptyVecs := semicolons.map (fun _ => emptyVec)
`(@Matrix.of (Fin $(quote semicolons.size)) (Fin 0) _ ![$emptyVecs,*])
| `(!![$[,%$commas]*]) => `(@Matrix.of (Fin 0) (Fin $(quote commas.size)) _ ![])
/-- Delaborator for the `!![]` notation. -/
@[app_delab DFunLike.coe]
def delabMatrixNotation : Delab := whenNotPPOption getPPExplicit <| whenPPOption getPPNotation <|
withOverApp 6 do
let mkApp3 (.const ``Matrix.of _) (.app (.const ``Fin _) em) (.app (.const ``Fin _) en) _ :=
(← getExpr).appFn!.appArg! | failure
let some m ← withNatValue em (pure ∘ some) | failure
let some n ← withNatValue en (pure ∘ some) | failure
withAppArg do
if m = 0 then
guard <| (← getExpr).isAppOfArity ``vecEmpty 1
let commas := .replicate n (mkAtom ",")
`(!![$[,%$commas]*])
else
if n = 0 then
let `(![$[![]%$evecs],*]) ← delab | failure
`(!![$[;%$evecs]*])
else
let `(![$[![$[$melems],*]],*]) ← delab | failure
`(!![$[$[$melems],*];*])
end Parser
variable (a b : ℕ)
/-- Use `![...]` notation for displaying a `Fin`-indexed matrix, for example:
```
#eval !![1, 2; 3, 4] + !![3, 4; 5, 6] -- !![4, 6; 8, 10]
```
-/
instance repr [Repr α] : Repr (Matrix (Fin m) (Fin n) α) where
reprPrec f _p :=
(Std.Format.bracket "!![" · "]") <|
(Std.Format.joinSep · (";" ++ Std.Format.line)) <|
(List.finRange m).map fun i =>
Std.Format.fill <| -- wrap line in a single place rather than all at once
(Std.Format.joinSep · ("," ++ Std.Format.line)) <|
(List.finRange n).map fun j => _root_.repr (f i j)
@[simp]
theorem cons_val' (v : n' → α) (B : Fin m → n' → α) (i j) :
vecCons v B i j = vecCons (v j) (fun i => B i j) i := by refine Fin.cases ?_ ?_ i <;> simp
@[simp]
theorem head_val' (B : Fin m.succ → n' → α) (j : n') : (vecHead fun i => B i j) = vecHead B j :=
rfl
@[simp]
theorem tail_val' (B : Fin m.succ → n' → α) (j : n') :
(vecTail fun i => B i j) = fun i => vecTail B i j := rfl
section DotProduct
variable [AddCommMonoid α] [Mul α]
@[simp]
theorem dotProduct_empty (v w : Fin 0 → α) : dotProduct v w = 0 :=
Finset.sum_empty
@[simp]
theorem cons_dotProduct (x : α) (v : Fin n → α) (w : Fin n.succ → α) :
dotProduct (vecCons x v) w = x * vecHead w + dotProduct v (vecTail w) := by
simp [dotProduct, Fin.sum_univ_succ, vecHead, vecTail]
@[simp]
theorem dotProduct_cons (v : Fin n.succ → α) (x : α) (w : Fin n → α) :
dotProduct v (vecCons x w) = vecHead v * x + dotProduct (vecTail v) w := by
simp [dotProduct, Fin.sum_univ_succ, vecHead, vecTail]
theorem cons_dotProduct_cons (x : α) (v : Fin n → α) (y : α) (w : Fin n → α) :
dotProduct (vecCons x v) (vecCons y w) = x * y + dotProduct v w := by simp
end DotProduct
section ColRow
variable {ι : Type*}
@[simp]
theorem replicateCol_empty (v : Fin 0 → α) : replicateCol ι v = vecEmpty :=
empty_eq _
@[deprecated (since := "2025-03-20")] alias col_empty := replicateCol_empty
@[simp]
theorem replicateCol_cons (x : α) (u : Fin m → α) :
replicateCol ι (vecCons x u) = of (vecCons (fun _ => x) (replicateCol ι u)) := by
ext i j
refine Fin.cases ?_ ?_ i <;> simp [vecHead, vecTail]
@[deprecated (since := "2025-03-20")] alias col_cons := replicateCol_cons
@[simp]
theorem replicateRow_empty : replicateRow ι (vecEmpty : Fin 0 → α) = of fun _ => vecEmpty := rfl
@[deprecated (since := "2025-03-20")] alias row_empty := replicateRow_empty
@[simp]
theorem replicateRow_cons (x : α) (u : Fin m → α) :
replicateRow ι (vecCons x u) = of fun _ => vecCons x u :=
rfl
@[deprecated (since := "2025-03-20")] alias row_cons := replicateRow_cons
end ColRow
section Transpose
@[simp]
theorem transpose_empty_rows (A : Matrix m' (Fin 0) α) : Aᵀ = of ![] :=
empty_eq _
@[simp]
theorem transpose_empty_cols (A : Matrix (Fin 0) m' α) : Aᵀ = of fun _ => ![] :=
funext fun _ => empty_eq _
@[simp]
theorem cons_transpose (v : n' → α) (A : Matrix (Fin m) n' α) :
(of (vecCons v A))ᵀ = of fun i => vecCons (v i) (Aᵀ i) := by
ext i j
refine Fin.cases ?_ ?_ j <;> simp
@[simp]
theorem head_transpose (A : Matrix m' (Fin n.succ) α) :
vecHead (of.symm Aᵀ) = vecHead ∘ of.symm A :=
rfl
@[simp]
theorem tail_transpose (A : Matrix m' (Fin n.succ) α) : vecTail (of.symm Aᵀ) = (vecTail ∘ A)ᵀ := by
ext i j
rfl
end Transpose
section Mul
variable [NonUnitalNonAssocSemiring α]
@[simp]
theorem empty_mul [Fintype n'] (A : Matrix (Fin 0) n' α) (B : Matrix n' o' α) : A * B = of ![] :=
empty_eq _
@[simp]
theorem empty_mul_empty (A : Matrix m' (Fin 0) α) (B : Matrix (Fin 0) o' α) : A * B = 0 :=
rfl
@[simp]
theorem mul_empty [Fintype n'] (A : Matrix m' n' α) (B : Matrix n' (Fin 0) α) :
A * B = of fun _ => ![] :=
funext fun _ => empty_eq _
theorem mul_val_succ [Fintype n'] (A : Matrix (Fin m.succ) n' α) (B : Matrix n' o' α) (i : Fin m)
(j : o') : (A * B) i.succ j = (of (vecTail (of.symm A)) * B) i j :=
rfl
@[simp]
theorem cons_mul [Fintype n'] (v : n' → α) (A : Fin m → n' → α) (B : Matrix n' o' α) :
of (vecCons v A) * B = of (vecCons (v ᵥ* B) (of.symm (of A * B))) := by
ext i j
refine Fin.cases ?_ ?_ i
· rfl
simp [mul_val_succ]
end Mul
section VecMul
variable [NonUnitalNonAssocSemiring α]
@[simp]
theorem empty_vecMul (v : Fin 0 → α) (B : Matrix (Fin 0) o' α) : v ᵥ* B = 0 :=
rfl
@[simp]
theorem vecMul_empty [Fintype n'] (v : n' → α) (B : Matrix n' (Fin 0) α) : v ᵥ* B = ![] :=
empty_eq _
@[simp]
theorem cons_vecMul (x : α) (v : Fin n → α) (B : Fin n.succ → o' → α) :
vecCons x v ᵥ* of B = x • vecHead B + v ᵥ* of (vecTail B) := by
ext i
simp [vecMul]
@[simp]
| Mathlib/Data/Matrix/Notation.lean | 305 | 306 | theorem vecMul_cons (v : Fin n.succ → α) (w : o' → α) (B : Fin n → o' → α) :
v ᵥ* of (vecCons w B) = vecHead v • w + vecTail v ᵥ* of B := by | |
/-
Copyright (c) 2020 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison
-/
import Mathlib.CategoryTheory.Limits.HasLimits
import Mathlib.CategoryTheory.Products.Basic
import Mathlib.CategoryTheory.Functor.Currying
import Mathlib.CategoryTheory.Products.Bifunctor
/-!
# A Fubini theorem for categorical (co)limits
We prove that $lim_{J × K} G = lim_J (lim_K G(j, -))$ for a functor `G : J × K ⥤ C`,
when all the appropriate limits exist.
We begin working with a functor `F : J ⥤ K ⥤ C`. We'll write `G : J × K ⥤ C` for the associated
"uncurried" functor.
In the first part, given a coherent family `D` of limit cones over the functors `F.obj j`,
and a cone `c` over `G`, we construct a cone over the cone points of `D`.
We then show that if `c` is a limit cone, the constructed cone is also a limit cone.
In the second part, we state the Fubini theorem in the setting where limits are
provided by suitable `HasLimit` classes.
We construct
`limitUncurryIsoLimitCompLim F : limit (uncurry.obj F) ≅ limit (F ⋙ lim)`
and give simp lemmas characterising it.
For convenience, we also provide
`limitIsoLimitCurryCompLim G : limit G ≅ limit ((curry.obj G) ⋙ lim)`
in terms of the uncurried functor.
All statements have their counterpart for colimits.
-/
open CategoryTheory
namespace CategoryTheory.Limits
variable {J K : Type*} [Category J] [Category K]
variable {C : Type*} [Category C]
variable (F : J ⥤ K ⥤ C) (G : J × K ⥤ C)
-- We could try introducing a "dependent functor type" to handle this?
/-- A structure carrying a diagram of cones over the functors `F.obj j`.
-/
structure DiagramOfCones where
/-- For each object, a cone. -/
obj : ∀ j : J, Cone (F.obj j)
/-- For each map, a map of cones. -/
map : ∀ {j j' : J} (f : j ⟶ j'), (Cones.postcompose (F.map f)).obj (obj j) ⟶ obj j'
id : ∀ j : J, (map (𝟙 j)).hom = 𝟙 _ := by aesop_cat
comp : ∀ {j₁ j₂ j₃ : J} (f : j₁ ⟶ j₂) (g : j₂ ⟶ j₃),
(map (f ≫ g)).hom = (map f).hom ≫ (map g).hom := by aesop_cat
/-- A structure carrying a diagram of cocones over the functors `F.obj j`.
-/
structure DiagramOfCocones where
/-- For each object, a cocone. -/
obj : ∀ j : J, Cocone (F.obj j)
/-- For each map, a map of cocones. -/
map : ∀ {j j' : J} (f : j ⟶ j'), (obj j) ⟶ (Cocones.precompose (F.map f)).obj (obj j')
id : ∀ j : J, (map (𝟙 j)).hom = 𝟙 _ := by aesop_cat
comp : ∀ {j₁ j₂ j₃ : J} (f : j₁ ⟶ j₂) (g : j₂ ⟶ j₃),
(map (f ≫ g)).hom = (map f).hom ≫ (map g).hom := by aesop_cat
variable {F}
/-- Extract the functor `J ⥤ C` consisting of the cone points and the maps between them,
from a `DiagramOfCones`.
-/
@[simps]
def DiagramOfCones.conePoints (D : DiagramOfCones F) : J ⥤ C where
obj j := (D.obj j).pt
map f := (D.map f).hom
map_id j := D.id j
map_comp f g := D.comp f g
/-- Extract the functor `J ⥤ C` consisting of the cocone points and the maps between them,
from a `DiagramOfCocones`.
-/
@[simps]
def DiagramOfCocones.coconePoints (D : DiagramOfCocones F) : J ⥤ C where
obj j := (D.obj j).pt
map f := (D.map f).hom
map_id j := D.id j
map_comp f g := D.comp f g
/-- Given a diagram `D` of limit cones over the `F.obj j`, and a cone over `uncurry.obj F`,
we can construct a cone over the diagram consisting of the cone points from `D`.
-/
@[simps]
def coneOfConeUncurry {D : DiagramOfCones F} (Q : ∀ j, IsLimit (D.obj j))
(c : Cone (uncurry.obj F)) : Cone D.conePoints where
pt := c.pt
π :=
{ app := fun j =>
(Q j).lift
{ pt := c.pt
π :=
{ app := fun k => c.π.app (j, k)
naturality := fun k k' f => by
dsimp; simp only [Category.id_comp]
have := @NatTrans.naturality _ _ _ _ _ _ c.π (j, k) (j, k') (𝟙 j, f)
dsimp at this
simp? at this says
simp only [Category.id_comp, Functor.map_id, NatTrans.id_app] at this
exact this } }
naturality := fun j j' f =>
(Q j').hom_ext
(by
dsimp
intro k
simp only [Limits.ConeMorphism.w, Limits.Cones.postcompose_obj_π,
Limits.IsLimit.fac_assoc, Limits.IsLimit.fac, NatTrans.comp_app, Category.id_comp,
Category.assoc]
have := @NatTrans.naturality _ _ _ _ _ _ c.π (j, k) (j', k) (f, 𝟙 k)
dsimp at this
simp only [Category.id_comp, Category.comp_id, CategoryTheory.Functor.map_id,
NatTrans.id_app] at this
exact this) }
/-- Given a diagram `D` of limit cones over the `curry.obj G j`, and a cone over `G`,
we can construct a cone over the diagram consisting of the cone points from `D`.
-/
@[simps]
def coneOfConeCurry {D : DiagramOfCones (curry.obj G)} (Q : ∀ j, IsLimit (D.obj j))
(c : Cone G) : Cone D.conePoints where
pt := c.pt
π :=
{ app j := (Q j).lift
{ pt := c.pt
π := { app k := c.π.app (j, k) } }
naturality {_ j'} _ := (Q j').hom_ext (by simp) }
/-- Given a diagram `D` of colimit cocones over the `F.obj j`, and a cocone over `uncurry.obj F`,
we can construct a cocone over the diagram consisting of the cocone points from `D`.
-/
@[simps]
def coconeOfCoconeUncurry {D : DiagramOfCocones F} (Q : ∀ j, IsColimit (D.obj j))
(c : Cocone (uncurry.obj F)) : Cocone D.coconePoints where
pt := c.pt
ι :=
{ app := fun j =>
(Q j).desc
{ pt := c.pt
ι :=
{ app := fun k => c.ι.app (j, k)
naturality := fun k k' f => by
dsimp; simp only [Category.comp_id]
conv_lhs =>
arg 1; equals (F.map (𝟙 _)).app _ ≫ (F.obj j).map f =>
simp
conv_lhs => arg 1; rw [← uncurry_obj_map F ((𝟙 j,f) : (j,k) ⟶ (j,k'))]
rw [c.w] } }
naturality := fun j j' f =>
(Q j).hom_ext
(by
dsimp
intro k
simp only [Limits.CoconeMorphism.w_assoc, Limits.Cocones.precompose_obj_ι,
Limits.IsColimit.fac_assoc, Limits.IsColimit.fac, NatTrans.comp_app, Category.comp_id,
Category.assoc]
have := @NatTrans.naturality _ _ _ _ _ _ c.ι (j, k) (j', k) (f, 𝟙 k)
dsimp at this
simp only [Category.id_comp, Category.comp_id, CategoryTheory.Functor.map_id,
NatTrans.id_app] at this
exact this) }
/-- Given a diagram `D` of colimit cocones under the `curry.obj G j`, and a cocone under `G`,
we can construct a cocone under the diagram consisting of the cocone points from `D`.
-/
@[simps]
def coconeOfCoconeCurry {D : DiagramOfCocones (curry.obj G)} (Q : ∀ j, IsColimit (D.obj j))
(c : Cocone G) : Cocone D.coconePoints where
pt := c.pt
ι :=
{ app j := (Q j).desc
{ pt := c.pt
ι := { app k := c.ι.app (j, k) } }
naturality {j _} _ := (Q j).hom_ext (by simp) }
/-- `coneOfConeUncurry Q c` is a limit cone when `c` is a limit cone.
-/
def coneOfConeUncurryIsLimit {D : DiagramOfCones F} (Q : ∀ j, IsLimit (D.obj j))
{c : Cone (uncurry.obj F)} (P : IsLimit c) : IsLimit (coneOfConeUncurry Q c) where
lift s :=
P.lift
{ pt := s.pt
π :=
{ app := fun p => s.π.app p.1 ≫ (D.obj p.1).π.app p.2
naturality := fun p p' f => by
dsimp; simp only [Category.id_comp, Category.assoc]
rcases p with ⟨j, k⟩
rcases p' with ⟨j', k'⟩
rcases f with ⟨fj, fk⟩
dsimp
slice_rhs 3 4 => rw [← NatTrans.naturality]
slice_rhs 2 3 => rw [← (D.obj j).π.naturality]
simp only [Functor.const_obj_map, Category.id_comp, Category.assoc]
have w := (D.map fj).w k'
dsimp at w
rw [← w]
have n := s.π.naturality fj
dsimp at n
simp only [Category.id_comp] at n
rw [n]
simp } }
fac s j := by
apply (Q j).hom_ext
intro k
simp
uniq s m w := by
refine P.uniq
{ pt := s.pt
π := _ } m ?_
rintro ⟨j, k⟩
dsimp
rw [← w j]
simp
/-- If `coneOfConeUncurry Q c` is a limit cone then `c` is in fact a limit cone.
-/
def IsLimit.ofConeOfConeUncurry {D : DiagramOfCones F} (Q : ∀ j, IsLimit (D.obj j))
{c : Cone (uncurry.obj F)} (P : IsLimit (coneOfConeUncurry Q c)) : IsLimit c :=
-- These constructions are used in various fields of the proof so we abstract them here.
letI E (j : J) : Prod.sectR j K ⋙ uncurry.obj F ≅ F.obj j :=
NatIso.ofComponents (fun _ ↦ Iso.refl _)
letI S (s : Cone (uncurry.obj F)) : Cone D.conePoints :=
{ pt := s.pt
π :=
{ app j := (Q j).lift <|
(Cones.postcompose (E j).hom).obj <| s.whisker (Prod.sectR j K)
naturality {j' j} f := (Q j).hom_ext <|
fun k ↦ by simpa [E] using s.π.naturality ((Prod.sectL J k).map f) } }
{ lift s := P.lift (S s)
fac s p := by
have h1 := (Q p.1).fac ((Cones.postcompose (E p.1).hom).obj <|
s.whisker (Prod.sectR p.1 K)) p.2
simp only [Functor.comp_obj, Prod.sectR_obj, uncurry_obj_obj, NatTrans.id_app,
Cones.postcompose_obj_pt, Cone.whisker_pt, Cones.postcompose_obj_π,
Cone.whisker_π, NatTrans.comp_app, Functor.const_obj_obj, whiskerLeft_app,
NatIso.ofComponents_hom_app, Iso.refl_hom, Category.comp_id, E] at h1
have h2 := (P.fac (S s) p.1)
dsimp only [Functor.comp_obj, Prod.sectR_obj, uncurry_obj_obj, NatTrans.id_app,
Functor.const_obj_obj, DiagramOfCones.conePoints_obj, DiagramOfCones.conePoints_map,
Functor.const_obj_map, id_eq, Cones.postcompose_obj_pt, Cone.whisker_pt,
Cones.postcompose_obj_π, Cone.whisker_π, NatTrans.comp_app, whiskerLeft_app,
NatIso.ofComponents_hom_app, Iso.refl_hom, Prod.sectL_obj, Prod.sectL_map, eq_mp_eq_cast,
eq_mpr_eq_cast, coneOfConeUncurry_pt, coneOfConeUncurry_π_app, S, E] at h2 ⊢
simp [← h1, ← h2]
uniq s f hf := P.uniq (s := S s) _ <|
fun j ↦ (Q j).hom_ext <| fun k ↦ by simpa [S, E] using hf (j, k) }
/-- `coconeOfCoconeUncurry Q c` is a colimit cocone when `c` is a colimit cocone.
-/
def coconeOfCoconeUncurryIsColimit {D : DiagramOfCocones F} (Q : ∀ j, IsColimit (D.obj j))
{c : Cocone (uncurry.obj F)} (P : IsColimit c) : IsColimit (coconeOfCoconeUncurry Q c) where
desc s :=
P.desc
{ pt := s.pt
ι :=
{ app := fun p => (D.obj p.1).ι.app p.2 ≫ s.ι.app p.1
naturality := fun p p' f => by
dsimp; simp only [Category.id_comp, Category.assoc]
rcases p with ⟨j, k⟩
rcases p' with ⟨j', k'⟩
rcases f with ⟨fj, fk⟩
dsimp
slice_lhs 2 3 => rw [(D.obj j').ι.naturality]
simp only [Functor.const_obj_map, Category.id_comp, Category.assoc]
have w := (D.map fj).w k
dsimp at w
slice_lhs 1 2 => rw [← w]
have n := s.ι.naturality fj
dsimp at n
simp only [Category.comp_id] at n
rw [← n]
simp } }
fac s j := by
apply (Q j).hom_ext
intro k
simp
uniq s m w := by
refine P.uniq
{ pt := s.pt
ι := _ } m ?_
rintro ⟨j, k⟩
dsimp
rw [← w j]
simp
/-- If `coconeOfCoconeUncurry Q c` is a colimit cocone then `c` is in fact a colimit
cocone. -/
def IsColimit.ofCoconeUncurry {D : DiagramOfCocones F}
(Q : ∀ j, IsColimit (D.obj j)) {c : Cocone (uncurry.obj F)}
(P : IsColimit (coconeOfCoconeUncurry Q c)) : IsColimit c :=
-- These constructions are used in various fields of the proof so we abstract them here.
letI E (j : J) : (Prod.sectR j K ⋙ uncurry.obj F ≅ F.obj j) :=
NatIso.ofComponents (fun _ ↦ Iso.refl _)
letI S (s : Cocone (uncurry.obj F)) : Cocone D.coconePoints :=
{ pt := s.pt
ι :=
{ app j := (Q j).desc <|
(Cocones.precompose (E j).inv).obj <| s.whisker (Prod.sectR j K)
naturality {j j'} f := (Q j).hom_ext <|
fun k ↦ by simpa [E] using s.ι.naturality ((Prod.sectL J k).map f) } }
{ desc s := P.desc (S s)
fac s p := by
have h1 := (Q p.1).fac ((Cocones.precompose (E p.1).inv).obj <|
s.whisker (Prod.sectR p.1 K)) p.2
simp only [Functor.comp_obj, Prod.sectR_obj, uncurry_obj_obj, NatTrans.id_app,
Cocones.precompose_obj_pt, Cocone.whisker_pt, Functor.const_obj_obj,
Cocones.precompose_obj_ι, Cocone.whisker_ι, NatTrans.comp_app, NatIso.ofComponents_inv_app,
Iso.refl_inv, whiskerLeft_app, Category.id_comp, E] at h1
have h2 := (P.fac (S s) p.1)
dsimp only [DiagramOfCocones.coconePoints_obj, Functor.comp_obj, Prod.sectR_obj,
uncurry_obj_obj, NatTrans.id_app, Functor.const_obj_obj, DiagramOfCocones.coconePoints_map,
Functor.const_obj_map, id_eq, Cocones.precompose_obj_pt, Cocone.whisker_pt,
Cocones.precompose_obj_ι, Cocone.whisker_ι, NatTrans.comp_app, NatIso.ofComponents_inv_app,
Iso.refl_inv, whiskerLeft_app, Prod.sectL_obj, Prod.sectL_map, eq_mp_eq_cast,
eq_mpr_eq_cast, coconeOfCoconeUncurry_pt, coconeOfCoconeUncurry_ι_app, S, E] at h2 ⊢
simp [← h1, ← h2]
uniq s f hf := P.uniq (s := S s) _ <|
fun j ↦ (Q j).hom_ext <| fun k ↦ by simpa [S, E] using hf (j, k) }
section
variable (F)
variable [HasLimitsOfShape K C]
/-- Given a functor `F : J ⥤ K ⥤ C`, with all needed limits,
we can construct a diagram consisting of the limit cone over each functor `F.obj j`,
and the universal cone morphisms between these.
-/
@[simps]
noncomputable def DiagramOfCones.mkOfHasLimits : DiagramOfCones F where
obj j := limit.cone (F.obj j)
map f := { hom := lim.map (F.map f) }
-- Satisfying the inhabited linter.
noncomputable instance diagramOfConesInhabited : Inhabited (DiagramOfCones F) :=
⟨DiagramOfCones.mkOfHasLimits F⟩
@[simp]
theorem DiagramOfCones.mkOfHasLimits_conePoints :
(DiagramOfCones.mkOfHasLimits F).conePoints = F ⋙ lim :=
rfl
section
variable [HasLimit (curry.obj G ⋙ lim)]
/-- Given a functor `G : J × K ⥤ C` such that `(curry.obj G ⋙ lim)` makes sense and has a limit,
we can construct a cone over `G` with `limit (curry.obj G ⋙ lim)` as a cone point -/
noncomputable def coneOfHasLimitCurryCompLim : Cone G :=
let Q : DiagramOfCones (curry.obj G) := .mkOfHasLimits _
{ pt := limit (curry.obj G ⋙ lim),
π :=
{ app x := limit.π (curry.obj G ⋙ lim) x.fst ≫ (Q.obj x.fst).π.app x.snd
naturality {x y} := fun ⟨f₁, f₂⟩ ↦ by
have := (Q.obj x.1).w f₂
dsimp [Q] at this ⊢
rw [← limit.w (F := curry.obj G ⋙ lim) (f := f₁)]
dsimp
simp only [Category.assoc, Category.id_comp, Prod.fac (f₁, f₂),
G.map_comp, limMap_π, curry_obj_map_app, reassoc_of% this] } }
/-- The cone `coneOfHasLimitCurryCompLim` is in fact a limit cone.
-/
noncomputable def isLimitConeOfHasLimitCurryCompLim : IsLimit (coneOfHasLimitCurryCompLim G) :=
let Q : DiagramOfCones (curry.obj G) := .mkOfHasLimits _
let Q' : ∀ j, IsLimit (Q.obj j) := fun j => limit.isLimit _
{ lift c' := limit.lift (F := curry.obj G ⋙ lim) (coneOfConeCurry G Q' c')
fac c' f := by simp [coneOfHasLimitCurryCompLim, Q, Q']
uniq c' f h := by
dsimp [coneOfHasLimitCurryCompLim] at f h ⊢
refine limit.hom_ext (F := curry.obj G ⋙ lim) (fun j ↦ limit.hom_ext (fun k ↦ ?_))
simp [h ⟨j, k⟩, Q'] }
/-- The functor `G` has a limit if `C` has `K`-shaped limits and `(curry.obj G ⋙ lim)` has a limit.
-/
instance : HasLimit G where
exists_limit :=
⟨ { cone := coneOfHasLimitCurryCompLim G
isLimit := isLimitConeOfHasLimitCurryCompLim G }⟩
end
variable [HasLimit (uncurry.obj F)] [HasLimit (F ⋙ lim)]
/-- The Fubini theorem for a functor `F : J ⥤ K ⥤ C`,
showing that the limit of `uncurry.obj F` can be computed as
the limit of the limits of the functors `F.obj j`.
-/
noncomputable def limitUncurryIsoLimitCompLim : limit (uncurry.obj F) ≅ limit (F ⋙ lim) := by
let c := limit.cone (uncurry.obj F)
let P : IsLimit c := limit.isLimit _
let G := DiagramOfCones.mkOfHasLimits F
let Q : ∀ j, IsLimit (G.obj j) := fun j => limit.isLimit _
have Q' := coneOfConeUncurryIsLimit Q P
have Q'' := limit.isLimit (F ⋙ lim)
exact IsLimit.conePointUniqueUpToIso Q' Q''
@[simp, reassoc]
theorem limitUncurryIsoLimitCompLim_hom_π_π {j} {k} :
(limitUncurryIsoLimitCompLim F).hom ≫ limit.π _ j ≫ limit.π _ k = limit.π _ (j, k) := by
dsimp [limitUncurryIsoLimitCompLim, IsLimit.conePointUniqueUpToIso, IsLimit.uniqueUpToIso]
simp
@[simp, reassoc]
| Mathlib/CategoryTheory/Limits/Fubini.lean | 414 | 420 | theorem limitUncurryIsoLimitCompLim_inv_π {j} {k} :
(limitUncurryIsoLimitCompLim F).inv ≫ limit.π _ (j, k) =
(limit.π _ j ≫ limit.π _ k) := by | rw [← cancel_epi (limitUncurryIsoLimitCompLim F).hom]
simp
end |
/-
Copyright (c) 2023 Josha Dekker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Josha Dekker
-/
import Mathlib.Topology.Bases
import Mathlib.Order.Filter.CountableInter
import Mathlib.Topology.Compactness.SigmaCompact
/-!
# Lindelöf sets and Lindelöf spaces
## Main definitions
We define the following properties for sets in a topological space:
* `IsLindelof s`: Two definitions are possible here. The more standard definition is that
every open cover that contains `s` contains a countable subcover. We choose for the equivalent
definition where we require that every nontrivial filter on `s` with the countable intersection
property has a clusterpoint. Equivalence is established in `isLindelof_iff_countable_subcover`.
* `LindelofSpace X`: `X` is Lindelöf if it is Lindelöf as a set.
* `NonLindelofSpace`: a space that is not a Lindëlof space, e.g. the Long Line.
## Main results
* `isLindelof_iff_countable_subcover`: A set is Lindelöf iff every open cover has a
countable subcover.
## Implementation details
* This API is mainly based on the API for IsCompact and follows notation and style as much
as possible.
-/
open Set Filter Topology TopologicalSpace
universe u v
variable {X : Type u} {Y : Type v} {ι : Type*}
variable [TopologicalSpace X] [TopologicalSpace Y] {s t : Set X}
section Lindelof
/-- A set `s` is Lindelöf if every nontrivial filter `f` with the countable intersection
property that contains `s`, has a clusterpoint in `s`. The filter-free definition is given by
`isLindelof_iff_countable_subcover`. -/
def IsLindelof (s : Set X) :=
∀ ⦃f⦄ [NeBot f] [CountableInterFilter f], f ≤ 𝓟 s → ∃ x ∈ s, ClusterPt x f
/-- The complement to a Lindelöf set belongs to a filter `f` with the countable intersection
property if it belongs to each filter `𝓝 x ⊓ f`, `x ∈ s`. -/
theorem IsLindelof.compl_mem_sets (hs : IsLindelof s) {f : Filter X} [CountableInterFilter f]
(hf : ∀ x ∈ s, sᶜ ∈ 𝓝 x ⊓ f) : sᶜ ∈ f := by
contrapose! hf
simp only [not_mem_iff_inf_principal_compl, compl_compl, inf_assoc] at hf ⊢
exact hs inf_le_right
/-- The complement to a Lindelöf set belongs to a filter `f` with the countable intersection
property if each `x ∈ s` has a neighborhood `t` within `s` such that `tᶜ` belongs to `f`. -/
theorem IsLindelof.compl_mem_sets_of_nhdsWithin (hs : IsLindelof s) {f : Filter X}
[CountableInterFilter f] (hf : ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, tᶜ ∈ f) : sᶜ ∈ f := by
refine hs.compl_mem_sets fun x hx ↦ ?_
rw [← disjoint_principal_right, disjoint_right_comm, (basis_sets _).disjoint_iff_left]
exact hf x hx
/-- If `p : Set X → Prop` is stable under restriction and union, and each point `x`
of a Lindelöf set `s` has a neighborhood `t` within `s` such that `p t`, then `p s` holds. -/
@[elab_as_elim]
theorem IsLindelof.induction_on (hs : IsLindelof s) {p : Set X → Prop}
(hmono : ∀ ⦃s t⦄, s ⊆ t → p t → p s)
(hcountable_union : ∀ (S : Set (Set X)), S.Countable → (∀ s ∈ S, p s) → p (⋃₀ S))
(hnhds : ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, p t) : p s := by
let f : Filter X := ofCountableUnion p hcountable_union (fun t ht _ hsub ↦ hmono hsub ht)
have : sᶜ ∈ f := hs.compl_mem_sets_of_nhdsWithin (by simpa [f] using hnhds)
rwa [← compl_compl s]
/-- The intersection of a Lindelöf set and a closed set is a Lindelöf set. -/
theorem IsLindelof.inter_right (hs : IsLindelof s) (ht : IsClosed t) : IsLindelof (s ∩ t) := by
intro f hnf _ hstf
rw [← inf_principal, le_inf_iff] at hstf
obtain ⟨x, hsx, hx⟩ : ∃ x ∈ s, ClusterPt x f := hs hstf.1
have hxt : x ∈ t := ht.mem_of_nhdsWithin_neBot <| hx.mono hstf.2
exact ⟨x, ⟨hsx, hxt⟩, hx⟩
/-- The intersection of a closed set and a Lindelöf set is a Lindelöf set. -/
theorem IsLindelof.inter_left (ht : IsLindelof t) (hs : IsClosed s) : IsLindelof (s ∩ t) :=
inter_comm t s ▸ ht.inter_right hs
/-- The set difference of a Lindelöf set and an open set is a Lindelöf set. -/
theorem IsLindelof.diff (hs : IsLindelof s) (ht : IsOpen t) : IsLindelof (s \ t) :=
hs.inter_right (isClosed_compl_iff.mpr ht)
/-- A closed subset of a Lindelöf set is a Lindelöf set. -/
theorem IsLindelof.of_isClosed_subset (hs : IsLindelof s) (ht : IsClosed t) (h : t ⊆ s) :
IsLindelof t := inter_eq_self_of_subset_right h ▸ hs.inter_right ht
/-- A continuous image of a Lindelöf set is a Lindelöf set. -/
theorem IsLindelof.image_of_continuousOn {f : X → Y} (hs : IsLindelof s) (hf : ContinuousOn f s) :
IsLindelof (f '' s) := by
intro l lne _ ls
have : NeBot (l.comap f ⊓ 𝓟 s) :=
comap_inf_principal_neBot_of_image_mem lne (le_principal_iff.1 ls)
obtain ⟨x, hxs, hx⟩ : ∃ x ∈ s, ClusterPt x (l.comap f ⊓ 𝓟 s) := @hs _ this _ inf_le_right
haveI := hx.neBot
use f x, mem_image_of_mem f hxs
have : Tendsto f (𝓝 x ⊓ (comap f l ⊓ 𝓟 s)) (𝓝 (f x) ⊓ l) := by
convert (hf x hxs).inf (@tendsto_comap _ _ f l) using 1
rw [nhdsWithin]
ac_rfl
exact this.neBot
/-- A continuous image of a Lindelöf set is a Lindelöf set within the codomain. -/
theorem IsLindelof.image {f : X → Y} (hs : IsLindelof s) (hf : Continuous f) :
IsLindelof (f '' s) := hs.image_of_continuousOn hf.continuousOn
/-- A filter with the countable intersection property that is finer than the principal filter on
a Lindelöf set `s` contains any open set that contains all clusterpoints of `s`. -/
theorem IsLindelof.adherence_nhdset {f : Filter X} [CountableInterFilter f] (hs : IsLindelof s)
(hf₂ : f ≤ 𝓟 s) (ht₁ : IsOpen t) (ht₂ : ∀ x ∈ s, ClusterPt x f → x ∈ t) : t ∈ f :=
(eq_or_neBot _).casesOn mem_of_eq_bot fun _ ↦
let ⟨x, hx, hfx⟩ := @hs (f ⊓ 𝓟 tᶜ) _ _ <| inf_le_of_left_le hf₂
have : x ∈ t := ht₂ x hx hfx.of_inf_left
have : tᶜ ∩ t ∈ 𝓝[tᶜ] x := inter_mem_nhdsWithin _ (ht₁.mem_nhds this)
have A : 𝓝[tᶜ] x = ⊥ := empty_mem_iff_bot.1 <| compl_inter_self t ▸ this
have : 𝓝[tᶜ] x ≠ ⊥ := hfx.of_inf_right.ne
absurd A this
/-- For every open cover of a Lindelöf set, there exists a countable subcover. -/
theorem IsLindelof.elim_countable_subcover {ι : Type v} (hs : IsLindelof s) (U : ι → Set X)
(hUo : ∀ i, IsOpen (U i)) (hsU : s ⊆ ⋃ i, U i) :
∃ r : Set ι, r.Countable ∧ (s ⊆ ⋃ i ∈ r, U i) := by
have hmono : ∀ ⦃s t : Set X⦄, s ⊆ t → (∃ r : Set ι, r.Countable ∧ t ⊆ ⋃ i ∈ r, U i)
→ (∃ r : Set ι, r.Countable ∧ s ⊆ ⋃ i ∈ r, U i) := by
intro _ _ hst ⟨r, ⟨hrcountable, hsub⟩⟩
exact ⟨r, hrcountable, Subset.trans hst hsub⟩
have hcountable_union : ∀ (S : Set (Set X)), S.Countable
→ (∀ s ∈ S, ∃ r : Set ι, r.Countable ∧ (s ⊆ ⋃ i ∈ r, U i))
→ ∃ r : Set ι, r.Countable ∧ (⋃₀ S ⊆ ⋃ i ∈ r, U i) := by
intro S hS hsr
choose! r hr using hsr
refine ⟨⋃ s ∈ S, r s, hS.biUnion_iff.mpr (fun s hs ↦ (hr s hs).1), ?_⟩
refine sUnion_subset ?h.right.h
simp only [mem_iUnion, exists_prop, iUnion_exists, biUnion_and']
exact fun i is x hx ↦ mem_biUnion is ((hr i is).2 hx)
have h_nhds : ∀ x ∈ s, ∃ t ∈ 𝓝[s] x, ∃ r : Set ι, r.Countable ∧ (t ⊆ ⋃ i ∈ r, U i) := by
intro x hx
let ⟨i, hi⟩ := mem_iUnion.1 (hsU hx)
refine ⟨U i, mem_nhdsWithin_of_mem_nhds ((hUo i).mem_nhds hi), {i}, by simp, ?_⟩
simp only [mem_singleton_iff, iUnion_iUnion_eq_left]
exact Subset.refl _
exact hs.induction_on hmono hcountable_union h_nhds
theorem IsLindelof.elim_nhds_subcover' (hs : IsLindelof s) (U : ∀ x ∈ s, Set X)
(hU : ∀ x (hx : x ∈ s), U x ‹x ∈ s› ∈ 𝓝 x) :
∃ t : Set s, t.Countable ∧ s ⊆ ⋃ x ∈ t, U (x : s) x.2 := by
have := hs.elim_countable_subcover (fun x : s ↦ interior (U x x.2)) (fun _ ↦ isOpen_interior)
fun x hx ↦
mem_iUnion.2 ⟨⟨x, hx⟩, mem_interior_iff_mem_nhds.2 <| hU _ _⟩
rcases this with ⟨r, ⟨hr, hs⟩⟩
use r, hr
apply Subset.trans hs
apply iUnion₂_subset
intro i hi
apply Subset.trans interior_subset
exact subset_iUnion_of_subset i (subset_iUnion_of_subset hi (Subset.refl _))
theorem IsLindelof.elim_nhds_subcover (hs : IsLindelof s) (U : X → Set X)
(hU : ∀ x ∈ s, U x ∈ 𝓝 x) :
∃ t : Set X, t.Countable ∧ (∀ x ∈ t, x ∈ s) ∧ s ⊆ ⋃ x ∈ t, U x := by
let ⟨t, ⟨htc, htsub⟩⟩ := hs.elim_nhds_subcover' (fun x _ ↦ U x) hU
refine ⟨↑t, Countable.image htc Subtype.val, ?_⟩
constructor
· intro _
simp only [mem_image, Subtype.exists, exists_and_right, exists_eq_right, forall_exists_index]
tauto
· have : ⋃ x ∈ t, U ↑x = ⋃ x ∈ Subtype.val '' t, U x := biUnion_image.symm
rwa [← this]
/-- For every nonempty open cover of a Lindelöf set, there exists a subcover indexed by ℕ. -/
theorem IsLindelof.indexed_countable_subcover {ι : Type v} [Nonempty ι]
(hs : IsLindelof s) (U : ι → Set X) (hUo : ∀ i, IsOpen (U i)) (hsU : s ⊆ ⋃ i, U i) :
∃ f : ℕ → ι, s ⊆ ⋃ n, U (f n) := by
obtain ⟨c, ⟨c_count, c_cov⟩⟩ := hs.elim_countable_subcover U hUo hsU
rcases c.eq_empty_or_nonempty with rfl | c_nonempty
· simp only [mem_empty_iff_false, iUnion_of_empty, iUnion_empty] at c_cov
simp only [subset_eq_empty c_cov rfl, empty_subset, exists_const]
obtain ⟨f, f_surj⟩ := (Set.countable_iff_exists_surjective c_nonempty).mp c_count
refine ⟨fun x ↦ f x, c_cov.trans <| iUnion₂_subset_iff.mpr (?_ : ∀ i ∈ c, U i ⊆ ⋃ n, U (f n))⟩
intro x hx
obtain ⟨n, hn⟩ := f_surj ⟨x, hx⟩
exact subset_iUnion_of_subset n <| subset_of_eq (by rw [hn])
/-- The neighborhood filter of a Lindelöf set is disjoint with a filter `l` with the countable
intersection property if and only if the neighborhood filter of each point of this set
is disjoint with `l`. -/
theorem IsLindelof.disjoint_nhdsSet_left {l : Filter X} [CountableInterFilter l]
(hs : IsLindelof s) :
Disjoint (𝓝ˢ s) l ↔ ∀ x ∈ s, Disjoint (𝓝 x) l := by
refine ⟨fun h x hx ↦ h.mono_left <| nhds_le_nhdsSet hx, fun H ↦ ?_⟩
choose! U hxU hUl using fun x hx ↦ (nhds_basis_opens x).disjoint_iff_left.1 (H x hx)
choose hxU hUo using hxU
rcases hs.elim_nhds_subcover U fun x hx ↦ (hUo x hx).mem_nhds (hxU x hx) with ⟨t, htc, hts, hst⟩
refine (hasBasis_nhdsSet _).disjoint_iff_left.2
⟨⋃ x ∈ t, U x, ⟨isOpen_biUnion fun x hx ↦ hUo x (hts x hx), hst⟩, ?_⟩
rw [compl_iUnion₂]
exact (countable_bInter_mem htc).mpr (fun i hi ↦ hUl _ (hts _ hi))
/-- A filter `l` with the countable intersection property is disjoint with the neighborhood
filter of a Lindelöf set if and only if it is disjoint with the neighborhood filter of each point
of this set. -/
theorem IsLindelof.disjoint_nhdsSet_right {l : Filter X} [CountableInterFilter l]
(hs : IsLindelof s) : Disjoint l (𝓝ˢ s) ↔ ∀ x ∈ s, Disjoint l (𝓝 x) := by
simpa only [disjoint_comm] using hs.disjoint_nhdsSet_left
/-- For every family of closed sets whose intersection avoids a Lindelö set,
there exists a countable subfamily whose intersection avoids this Lindelöf set. -/
theorem IsLindelof.elim_countable_subfamily_closed {ι : Type v} (hs : IsLindelof s)
(t : ι → Set X) (htc : ∀ i, IsClosed (t i)) (hst : (s ∩ ⋂ i, t i) = ∅) :
∃ u : Set ι, u.Countable ∧ (s ∩ ⋂ i ∈ u, t i) = ∅ := by
let U := tᶜ
have hUo : ∀ i, IsOpen (U i) := by simp only [U, Pi.compl_apply, isOpen_compl_iff]; exact htc
have hsU : s ⊆ ⋃ i, U i := by
simp only [U, Pi.compl_apply]
rw [← compl_iInter]
apply disjoint_compl_left_iff_subset.mp
simp only [compl_iInter, compl_iUnion, compl_compl]
apply Disjoint.symm
exact disjoint_iff_inter_eq_empty.mpr hst
rcases hs.elim_countable_subcover U hUo hsU with ⟨u, ⟨hucount, husub⟩⟩
use u, hucount
rw [← disjoint_compl_left_iff_subset] at husub
simp only [U, Pi.compl_apply, compl_iUnion, compl_compl] at husub
exact disjoint_iff_inter_eq_empty.mp (Disjoint.symm husub)
/-- To show that a Lindelöf set intersects the intersection of a family of closed sets,
it is sufficient to show that it intersects every countable subfamily. -/
theorem IsLindelof.inter_iInter_nonempty {ι : Type v} (hs : IsLindelof s) (t : ι → Set X)
(htc : ∀ i, IsClosed (t i)) (hst : ∀ u : Set ι, u.Countable ∧ (s ∩ ⋂ i ∈ u, t i).Nonempty) :
(s ∩ ⋂ i, t i).Nonempty := by
contrapose! hst
rcases hs.elim_countable_subfamily_closed t htc hst with ⟨u, ⟨_, husub⟩⟩
exact ⟨u, fun _ ↦ husub⟩
/-- For every open cover of a Lindelöf set, there exists a countable subcover. -/
theorem IsLindelof.elim_countable_subcover_image {b : Set ι} {c : ι → Set X} (hs : IsLindelof s)
(hc₁ : ∀ i ∈ b, IsOpen (c i)) (hc₂ : s ⊆ ⋃ i ∈ b, c i) :
∃ b', b' ⊆ b ∧ Set.Countable b' ∧ s ⊆ ⋃ i ∈ b', c i := by
simp only [Subtype.forall', biUnion_eq_iUnion] at hc₁ hc₂
rcases hs.elim_countable_subcover (fun i ↦ c i : b → Set X) hc₁ hc₂ with ⟨d, hd⟩
refine ⟨Subtype.val '' d, by simp, Countable.image hd.1 Subtype.val, ?_⟩
rw [biUnion_image]
exact hd.2
/-- A set `s` is Lindelöf if for every open cover of `s`, there exists a countable subcover. -/
theorem isLindelof_of_countable_subcover
(h : ∀ {ι : Type u} (U : ι → Set X), (∀ i, IsOpen (U i)) → (s ⊆ ⋃ i, U i) →
∃ t : Set ι, t.Countable ∧ s ⊆ ⋃ i ∈ t, U i) :
IsLindelof s := fun f hf hfs ↦ by
contrapose! h
simp only [ClusterPt, not_neBot, ← disjoint_iff, SetCoe.forall',
(nhds_basis_opens _).disjoint_iff_left] at h
choose fsub U hU hUf using h
refine ⟨s, U, fun x ↦ (hU x).2, fun x hx ↦ mem_iUnion.2 ⟨⟨x, hx⟩, (hU _).1 ⟩, ?_⟩
intro t ht h
have uinf := f.sets_of_superset (le_principal_iff.1 fsub) h
have uninf : ⋂ i ∈ t, (U i)ᶜ ∈ f := (countable_bInter_mem ht).mpr (fun _ _ ↦ hUf _)
rw [← compl_iUnion₂] at uninf
have uninf := compl_not_mem uninf
simp only [compl_compl] at uninf
contradiction
/-- A set `s` is Lindelöf if for every family of closed sets whose intersection avoids `s`,
there exists a countable subfamily whose intersection avoids `s`. -/
theorem isLindelof_of_countable_subfamily_closed
(h :
∀ {ι : Type u} (t : ι → Set X), (∀ i, IsClosed (t i)) → (s ∩ ⋂ i, t i) = ∅ →
∃ u : Set ι, u.Countable ∧ (s ∩ ⋂ i ∈ u, t i) = ∅) :
IsLindelof s :=
isLindelof_of_countable_subcover fun U hUo hsU ↦ by
rw [← disjoint_compl_right_iff_subset, compl_iUnion, disjoint_iff] at hsU
rcases h (fun i ↦ (U i)ᶜ) (fun i ↦ (hUo _).isClosed_compl) hsU with ⟨t, ht⟩
refine ⟨t, ?_⟩
rwa [← disjoint_compl_right_iff_subset, compl_iUnion₂, disjoint_iff]
/-- A set `s` is Lindelöf if and only if
for every open cover of `s`, there exists a countable subcover. -/
theorem isLindelof_iff_countable_subcover :
IsLindelof s ↔ ∀ {ι : Type u} (U : ι → Set X),
(∀ i, IsOpen (U i)) → (s ⊆ ⋃ i, U i) → ∃ t : Set ι, t.Countable ∧ s ⊆ ⋃ i ∈ t, U i :=
⟨fun hs ↦ hs.elim_countable_subcover, isLindelof_of_countable_subcover⟩
/-- A set `s` is Lindelöf if and only if
for every family of closed sets whose intersection avoids `s`,
there exists a countable subfamily whose intersection avoids `s`. -/
theorem isLindelof_iff_countable_subfamily_closed :
IsLindelof s ↔ ∀ {ι : Type u} (t : ι → Set X),
(∀ i, IsClosed (t i)) → (s ∩ ⋂ i, t i) = ∅
→ ∃ u : Set ι, u.Countable ∧ (s ∩ ⋂ i ∈ u, t i) = ∅ :=
⟨fun hs ↦ hs.elim_countable_subfamily_closed, isLindelof_of_countable_subfamily_closed⟩
/-- The empty set is a Lindelof set. -/
@[simp]
theorem isLindelof_empty : IsLindelof (∅ : Set X) := fun _f hnf _ hsf ↦
Not.elim hnf.ne <| empty_mem_iff_bot.1 <| le_principal_iff.1 hsf
/-- A singleton set is a Lindelof set. -/
@[simp]
theorem isLindelof_singleton {x : X} : IsLindelof ({x} : Set X) := fun _ hf _ hfa ↦
⟨x, rfl, ClusterPt.of_le_nhds'
(hfa.trans <| by simpa only [principal_singleton] using pure_le_nhds x) hf⟩
theorem Set.Subsingleton.isLindelof (hs : s.Subsingleton) : IsLindelof s :=
Subsingleton.induction_on hs isLindelof_empty fun _ ↦ isLindelof_singleton
theorem Set.Countable.isLindelof_biUnion {s : Set ι} {f : ι → Set X} (hs : s.Countable)
(hf : ∀ i ∈ s, IsLindelof (f i)) : IsLindelof (⋃ i ∈ s, f i) := by
apply isLindelof_of_countable_subcover
intro i U hU hUcover
have hiU : ∀ i ∈ s, f i ⊆ ⋃ i, U i :=
fun _ is ↦ _root_.subset_trans (subset_biUnion_of_mem is) hUcover
have iSets := fun i is ↦ (hf i is).elim_countable_subcover U hU (hiU i is)
choose! r hr using iSets
use ⋃ i ∈ s, r i
constructor
· refine (Countable.biUnion_iff hs).mpr ?h.left.a
exact fun s hs ↦ (hr s hs).1
· refine iUnion₂_subset ?h.right.h
intro i is
simp only [mem_iUnion, exists_prop, iUnion_exists, biUnion_and']
intro x hx
exact mem_biUnion is ((hr i is).2 hx)
theorem Set.Finite.isLindelof_biUnion {s : Set ι} {f : ι → Set X} (hs : s.Finite)
(hf : ∀ i ∈ s, IsLindelof (f i)) : IsLindelof (⋃ i ∈ s, f i) :=
Set.Countable.isLindelof_biUnion (countable hs) hf
theorem Finset.isLindelof_biUnion (s : Finset ι) {f : ι → Set X} (hf : ∀ i ∈ s, IsLindelof (f i)) :
IsLindelof (⋃ i ∈ s, f i) :=
s.finite_toSet.isLindelof_biUnion hf
theorem isLindelof_accumulate {K : ℕ → Set X} (hK : ∀ n, IsLindelof (K n)) (n : ℕ) :
IsLindelof (Accumulate K n) :=
(finite_le_nat n).isLindelof_biUnion fun k _ => hK k
theorem Set.Countable.isLindelof_sUnion {S : Set (Set X)} (hf : S.Countable)
(hc : ∀ s ∈ S, IsLindelof s) : IsLindelof (⋃₀ S) := by
rw [sUnion_eq_biUnion]; exact hf.isLindelof_biUnion hc
theorem Set.Finite.isLindelof_sUnion {S : Set (Set X)} (hf : S.Finite)
(hc : ∀ s ∈ S, IsLindelof s) : IsLindelof (⋃₀ S) := by
rw [sUnion_eq_biUnion]; exact hf.isLindelof_biUnion hc
theorem isLindelof_iUnion {ι : Sort*} {f : ι → Set X} [Countable ι] (h : ∀ i, IsLindelof (f i)) :
IsLindelof (⋃ i, f i) := (countable_range f).isLindelof_sUnion <| forall_mem_range.2 h
theorem Set.Countable.isLindelof (hs : s.Countable) : IsLindelof s :=
biUnion_of_singleton s ▸ hs.isLindelof_biUnion fun _ _ => isLindelof_singleton
theorem Set.Finite.isLindelof (hs : s.Finite) : IsLindelof s :=
biUnion_of_singleton s ▸ hs.isLindelof_biUnion fun _ _ => isLindelof_singleton
theorem IsLindelof.countable_of_discrete [DiscreteTopology X] (hs : IsLindelof s) :
s.Countable := by
have : ∀ x : X, ({x} : Set X) ∈ 𝓝 x := by simp [nhds_discrete]
rcases hs.elim_nhds_subcover (fun x => {x}) fun x _ => this x with ⟨t, ht, _, hssubt⟩
rw [biUnion_of_singleton] at hssubt
exact ht.mono hssubt
theorem isLindelof_iff_countable [DiscreteTopology X] : IsLindelof s ↔ s.Countable :=
⟨fun h => h.countable_of_discrete, fun h => h.isLindelof⟩
theorem IsLindelof.union (hs : IsLindelof s) (ht : IsLindelof t) : IsLindelof (s ∪ t) := by
rw [union_eq_iUnion]; exact isLindelof_iUnion fun b => by cases b <;> assumption
protected theorem IsLindelof.insert (hs : IsLindelof s) (a) : IsLindelof (insert a s) :=
isLindelof_singleton.union hs
/-- If `X` has a basis consisting of compact opens, then an open set in `X` is compact open iff
it is a finite union of some elements in the basis -/
theorem isLindelof_open_iff_eq_countable_iUnion_of_isTopologicalBasis (b : ι → Set X)
(hb : IsTopologicalBasis (Set.range b)) (hb' : ∀ i, IsLindelof (b i)) (U : Set X) :
IsLindelof U ∧ IsOpen U ↔ ∃ s : Set ι, s.Countable ∧ U = ⋃ i ∈ s, b i := by
constructor
· rintro ⟨h₁, h₂⟩
obtain ⟨Y, f, rfl, hf⟩ := hb.open_eq_iUnion h₂
choose f' hf' using hf
have : b ∘ f' = f := funext hf'
subst this
obtain ⟨t, ht⟩ :=
h₁.elim_countable_subcover (b ∘ f') (fun i => hb.isOpen (Set.mem_range_self _)) Subset.rfl
refine ⟨t.image f', Countable.image (ht.1) f', le_antisymm ?_ ?_⟩
· refine Set.Subset.trans ht.2 ?_
simp only [Set.iUnion_subset_iff]
intro i hi
rw [← Set.iUnion_subtype (fun x : ι => x ∈ t.image f') fun i => b i.1]
exact Set.subset_iUnion (fun i : t.image f' => b i) ⟨_, mem_image_of_mem _ hi⟩
· apply Set.iUnion₂_subset
rintro i hi
obtain ⟨j, -, rfl⟩ := (mem_image ..).mp hi
exact Set.subset_iUnion (b ∘ f') j
· rintro ⟨s, hs, rfl⟩
constructor
· exact hs.isLindelof_biUnion fun i _ => hb' i
· exact isOpen_biUnion fun i _ => hb.isOpen (Set.mem_range_self _)
/-- `Filter.coLindelof` is the filter generated by complements to Lindelöf sets. -/
def Filter.coLindelof (X : Type*) [TopologicalSpace X] : Filter X :=
--`Filter.coLindelof` is the filter generated by complements to Lindelöf sets.
⨅ (s : Set X) (_ : IsLindelof s), 𝓟 sᶜ
theorem hasBasis_coLindelof : (coLindelof X).HasBasis IsLindelof compl :=
hasBasis_biInf_principal'
(fun s hs t ht =>
⟨s ∪ t, hs.union ht, compl_subset_compl.2 subset_union_left,
compl_subset_compl.2 subset_union_right⟩)
⟨∅, isLindelof_empty⟩
theorem mem_coLindelof : s ∈ coLindelof X ↔ ∃ t, IsLindelof t ∧ tᶜ ⊆ s :=
hasBasis_coLindelof.mem_iff
theorem mem_coLindelof' : s ∈ coLindelof X ↔ ∃ t, IsLindelof t ∧ sᶜ ⊆ t :=
mem_coLindelof.trans <| exists_congr fun _ => and_congr_right fun _ => compl_subset_comm
theorem _root_.IsLindelof.compl_mem_coLindelof (hs : IsLindelof s) : sᶜ ∈ coLindelof X :=
hasBasis_coLindelof.mem_of_mem hs
theorem coLindelof_le_cofinite : coLindelof X ≤ cofinite := fun s hs =>
compl_compl s ▸ hs.isLindelof.compl_mem_coLindelof
theorem Tendsto.isLindelof_insert_range_of_coLindelof {f : X → Y} {y}
(hf : Tendsto f (coLindelof X) (𝓝 y)) (hfc : Continuous f) :
IsLindelof (insert y (range f)) := by
intro l hne _ hle
by_cases hy : ClusterPt y l
· exact ⟨y, Or.inl rfl, hy⟩
simp only [clusterPt_iff_nonempty, not_forall, ← not_disjoint_iff_nonempty_inter, not_not] at hy
rcases hy with ⟨s, hsy, t, htl, hd⟩
rcases mem_coLindelof.1 (hf hsy) with ⟨K, hKc, hKs⟩
have : f '' K ∈ l := by
filter_upwards [htl, le_principal_iff.1 hle] with y hyt hyf
rcases hyf with (rfl | ⟨x, rfl⟩)
exacts [(hd.le_bot ⟨mem_of_mem_nhds hsy, hyt⟩).elim,
mem_image_of_mem _ (not_not.1 fun hxK => hd.le_bot ⟨hKs hxK, hyt⟩)]
rcases hKc.image hfc (le_principal_iff.2 this) with ⟨y, hy, hyl⟩
exact ⟨y, Or.inr <| image_subset_range _ _ hy, hyl⟩
/-- `Filter.coclosedLindelof` is the filter generated by complements to closed Lindelof sets. -/
def Filter.coclosedLindelof (X : Type*) [TopologicalSpace X] : Filter X :=
-- `Filter.coclosedLindelof` is the filter generated by complements to closed Lindelof sets.
⨅ (s : Set X) (_ : IsClosed s) (_ : IsLindelof s), 𝓟 sᶜ
theorem hasBasis_coclosedLindelof :
(Filter.coclosedLindelof X).HasBasis (fun s => IsClosed s ∧ IsLindelof s) compl := by
simp only [Filter.coclosedLindelof, iInf_and']
refine hasBasis_biInf_principal' ?_ ⟨∅, isClosed_empty, isLindelof_empty⟩
rintro s ⟨hs₁, hs₂⟩ t ⟨ht₁, ht₂⟩
exact ⟨s ∪ t, ⟨⟨hs₁.union ht₁, hs₂.union ht₂⟩, compl_subset_compl.2 subset_union_left,
compl_subset_compl.2 subset_union_right⟩⟩
theorem mem_coclosedLindelof : s ∈ coclosedLindelof X ↔
∃ t, IsClosed t ∧ IsLindelof t ∧ tᶜ ⊆ s := by
simp only [hasBasis_coclosedLindelof.mem_iff, and_assoc]
theorem mem_coclosed_Lindelof' : s ∈ coclosedLindelof X ↔
∃ t, IsClosed t ∧ IsLindelof t ∧ sᶜ ⊆ t := by
simp only [mem_coclosedLindelof, compl_subset_comm]
theorem coLindelof_le_coclosedLindelof : coLindelof X ≤ coclosedLindelof X :=
iInf_mono fun _ => le_iInf fun _ => le_rfl
theorem IsLindeof.compl_mem_coclosedLindelof_of_isClosed (hs : IsLindelof s) (hs' : IsClosed s) :
sᶜ ∈ Filter.coclosedLindelof X :=
hasBasis_coclosedLindelof.mem_of_mem ⟨hs', hs⟩
/-- X is a Lindelöf space iff every open cover has a countable subcover. -/
class LindelofSpace (X : Type*) [TopologicalSpace X] : Prop where
/-- In a Lindelöf space, `Set.univ` is a Lindelöf set. -/
isLindelof_univ : IsLindelof (univ : Set X)
instance (priority := 10) Subsingleton.lindelofSpace [Subsingleton X] : LindelofSpace X :=
⟨subsingleton_univ.isLindelof⟩
theorem isLindelof_univ_iff : IsLindelof (univ : Set X) ↔ LindelofSpace X :=
⟨fun h => ⟨h⟩, fun h => h.1⟩
theorem isLindelof_univ [h : LindelofSpace X] : IsLindelof (univ : Set X) :=
h.isLindelof_univ
theorem cluster_point_of_Lindelof [LindelofSpace X] (f : Filter X) [NeBot f]
[CountableInterFilter f] : ∃ x, ClusterPt x f := by
simpa using isLindelof_univ (show f ≤ 𝓟 univ by simp)
theorem LindelofSpace.elim_nhds_subcover [LindelofSpace X] (U : X → Set X) (hU : ∀ x, U x ∈ 𝓝 x) :
∃ t : Set X, t.Countable ∧ ⋃ x ∈ t, U x = univ := by
obtain ⟨t, tc, -, s⟩ := IsLindelof.elim_nhds_subcover isLindelof_univ U fun x _ => hU x
use t, tc
apply top_unique s
theorem lindelofSpace_of_countable_subfamily_closed
(h : ∀ {ι : Type u} (t : ι → Set X), (∀ i, IsClosed (t i)) → ⋂ i, t i = ∅ →
∃ u : Set ι, u.Countable ∧ ⋂ i ∈ u, t i = ∅) :
LindelofSpace X where
isLindelof_univ := isLindelof_of_countable_subfamily_closed fun t => by simpa using h t
theorem IsClosed.isLindelof [LindelofSpace X] (h : IsClosed s) : IsLindelof s :=
isLindelof_univ.of_isClosed_subset h (subset_univ _)
/-- A compact set `s` is Lindelöf. -/
theorem IsCompact.isLindelof (hs : IsCompact s) :
IsLindelof s := by tauto
/-- A σ-compact set `s` is Lindelöf -/
theorem IsSigmaCompact.isLindelof (hs : IsSigmaCompact s) :
IsLindelof s := by
rw [IsSigmaCompact] at hs
rcases hs with ⟨K, ⟨hc, huniv⟩⟩
rw [← huniv]
have hl : ∀ n, IsLindelof (K n) := fun n ↦ IsCompact.isLindelof (hc n)
exact isLindelof_iUnion hl
/-- A compact space `X` is Lindelöf. -/
instance (priority := 100) [CompactSpace X] : LindelofSpace X :=
{ isLindelof_univ := isCompact_univ.isLindelof}
/-- A sigma-compact space `X` is Lindelöf. -/
instance (priority := 100) [SigmaCompactSpace X] : LindelofSpace X :=
{ isLindelof_univ := isSigmaCompact_univ.isLindelof}
/-- `X` is a non-Lindelöf topological space if it is not a Lindelöf space. -/
class NonLindelofSpace (X : Type*) [TopologicalSpace X] : Prop where
/-- In a non-Lindelöf space, `Set.univ` is not a Lindelöf set. -/
nonLindelof_univ : ¬IsLindelof (univ : Set X)
lemma nonLindelof_univ (X : Type*) [TopologicalSpace X] [NonLindelofSpace X] :
¬IsLindelof (univ : Set X) :=
NonLindelofSpace.nonLindelof_univ
theorem IsLindelof.ne_univ [NonLindelofSpace X] (hs : IsLindelof s) : s ≠ univ := fun h ↦
nonLindelof_univ X (h ▸ hs)
instance [NonLindelofSpace X] : NeBot (Filter.coLindelof X) := by
refine hasBasis_coLindelof.neBot_iff.2 fun {s} hs => ?_
contrapose hs
rw [not_nonempty_iff_eq_empty, compl_empty_iff] at hs
rw [hs]
exact nonLindelof_univ X
@[simp]
theorem Filter.coLindelof_eq_bot [LindelofSpace X] : Filter.coLindelof X = ⊥ :=
hasBasis_coLindelof.eq_bot_iff.mpr ⟨Set.univ, isLindelof_univ, Set.compl_univ⟩
instance [NonLindelofSpace X] : NeBot (Filter.coclosedLindelof X) :=
neBot_of_le coLindelof_le_coclosedLindelof
theorem nonLindelofSpace_of_neBot (_ : NeBot (Filter.coLindelof X)) : NonLindelofSpace X :=
⟨fun h' => (Filter.nonempty_of_mem h'.compl_mem_coLindelof).ne_empty compl_univ⟩
theorem Filter.coLindelof_neBot_iff : NeBot (Filter.coLindelof X) ↔ NonLindelofSpace X :=
⟨nonLindelofSpace_of_neBot, fun _ => inferInstance⟩
theorem not_LindelofSpace_iff : ¬LindelofSpace X ↔ NonLindelofSpace X :=
⟨fun h₁ => ⟨fun h₂ => h₁ ⟨h₂⟩⟩, fun ⟨h₁⟩ ⟨h₂⟩ => h₁ h₂⟩
/-- A compact space `X` is Lindelöf. -/
instance (priority := 100) [CompactSpace X] : LindelofSpace X :=
{ isLindelof_univ := isCompact_univ.isLindelof}
theorem countable_of_Lindelof_of_discrete [LindelofSpace X] [DiscreteTopology X] : Countable X :=
countable_univ_iff.mp isLindelof_univ.countable_of_discrete
theorem countable_cover_nhds_interior [LindelofSpace X] {U : X → Set X} (hU : ∀ x, U x ∈ 𝓝 x) :
∃ t : Set X, t.Countable ∧ ⋃ x ∈ t, interior (U x) = univ :=
let ⟨t, ht⟩ := isLindelof_univ.elim_countable_subcover (fun x => interior (U x))
(fun _ => isOpen_interior) fun x _ => mem_iUnion.2 ⟨x, mem_interior_iff_mem_nhds.2 (hU x)⟩
⟨t, ⟨ht.1, univ_subset_iff.1 ht.2⟩⟩
theorem countable_cover_nhds [LindelofSpace X] {U : X → Set X} (hU : ∀ x, U x ∈ 𝓝 x) :
∃ t : Set X, t.Countable ∧ ⋃ x ∈ t, U x = univ :=
let ⟨t, ht⟩ := countable_cover_nhds_interior hU
⟨t, ⟨ht.1, univ_subset_iff.1 <| ht.2.symm.subset.trans <|
iUnion₂_mono fun _ _ => interior_subset⟩⟩
/-- The comap of the coLindelöf filter on `Y` by a continuous function `f : X → Y` is less than or
equal to the coLindelöf filter on `X`.
This is a reformulation of the fact that images of Lindelöf sets are Lindelöf. -/
theorem Filter.comap_coLindelof_le {f : X → Y} (hf : Continuous f) :
(Filter.coLindelof Y).comap f ≤ Filter.coLindelof X := by
rw [(hasBasis_coLindelof.comap f).le_basis_iff hasBasis_coLindelof]
intro t ht
refine ⟨f '' t, ht.image hf, ?_⟩
simpa using t.subset_preimage_image f
| Mathlib/Topology/Compactness/Lindelof.lean | 596 | 597 | theorem isLindelof_range [LindelofSpace X] {f : X → Y} (hf : Continuous f) :
IsLindelof (range f) := by | rw [← image_univ]; exact isLindelof_univ.image hf |
/-
Copyright (c) 2019 Gabriel Ebner. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Gabriel Ebner, Sébastien Gouëzel, Yury Kudryashov, Anatole Dedecker
-/
import Mathlib.Analysis.Calculus.Deriv.Basic
import Mathlib.Analysis.Calculus.FDeriv.Add
/-!
# One-dimensional derivatives of sums etc
In this file we prove formulas about derivatives of `f + g`, `-f`, `f - g`, and `∑ i, f i x` for
functions from the base field to a normed space over this field.
For a more detailed overview of one-dimensional derivatives in mathlib, see the module docstring of
`Analysis/Calculus/Deriv/Basic`.
## Keywords
derivative
-/
universe u v w
open scoped Topology Filter ENNReal
open Asymptotics Set
variable {𝕜 : Type u} [NontriviallyNormedField 𝕜]
variable {F : Type v} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
variable {f g : 𝕜 → F}
variable {f' g' : F}
variable {x : 𝕜} {s : Set 𝕜} {L : Filter 𝕜}
section Add
/-! ### Derivative of the sum of two functions -/
nonrec theorem HasDerivAtFilter.add (hf : HasDerivAtFilter f f' x L)
(hg : HasDerivAtFilter g g' x L) : HasDerivAtFilter (fun y => f y + g y) (f' + g') x L := by
simpa using (hf.add hg).hasDerivAtFilter
nonrec theorem HasStrictDerivAt.add (hf : HasStrictDerivAt f f' x) (hg : HasStrictDerivAt g g' x) :
HasStrictDerivAt (fun y => f y + g y) (f' + g') x := by simpa using (hf.add hg).hasStrictDerivAt
nonrec theorem HasDerivWithinAt.add (hf : HasDerivWithinAt f f' s x)
(hg : HasDerivWithinAt g g' s x) : HasDerivWithinAt (fun y => f y + g y) (f' + g') s x :=
hf.add hg
nonrec theorem HasDerivAt.add (hf : HasDerivAt f f' x) (hg : HasDerivAt g g' x) :
HasDerivAt (fun x => f x + g x) (f' + g') x :=
hf.add hg
theorem derivWithin_add (hf : DifferentiableWithinAt 𝕜 f s x)
(hg : DifferentiableWithinAt 𝕜 g s x) :
derivWithin (fun y => f y + g y) s x = derivWithin f s x + derivWithin g s x := by
by_cases hsx : UniqueDiffWithinAt 𝕜 s x
· exact (hf.hasDerivWithinAt.add hg.hasDerivWithinAt).derivWithin hsx
· simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx]
@[simp]
theorem deriv_add (hf : DifferentiableAt 𝕜 f x) (hg : DifferentiableAt 𝕜 g x) :
deriv (fun y => f y + g y) x = deriv f x + deriv g x :=
(hf.hasDerivAt.add hg.hasDerivAt).deriv
@[simp]
theorem hasDerivAtFilter_add_const_iff (c : F) :
HasDerivAtFilter (f · + c) f' x L ↔ HasDerivAtFilter f f' x L :=
hasFDerivAtFilter_add_const_iff c
alias ⟨_, HasDerivAtFilter.add_const⟩ := hasDerivAtFilter_add_const_iff
@[simp]
theorem hasStrictDerivAt_add_const_iff (c : F) :
HasStrictDerivAt (f · + c) f' x ↔ HasStrictDerivAt f f' x :=
hasStrictFDerivAt_add_const_iff c
alias ⟨_, HasStrictDerivAt.add_const⟩ := hasStrictDerivAt_add_const_iff
@[simp]
theorem hasDerivWithinAt_add_const_iff (c : F) :
HasDerivWithinAt (f · + c) f' s x ↔ HasDerivWithinAt f f' s x :=
hasDerivAtFilter_add_const_iff c
alias ⟨_, HasDerivWithinAt.add_const⟩ := hasDerivWithinAt_add_const_iff
@[simp]
theorem hasDerivAt_add_const_iff (c : F) : HasDerivAt (f · + c) f' x ↔ HasDerivAt f f' x :=
hasDerivAtFilter_add_const_iff c
alias ⟨_, HasDerivAt.add_const⟩ := hasDerivAt_add_const_iff
theorem derivWithin_add_const (c : F) :
derivWithin (fun y => f y + c) s x = derivWithin f s x := by
simp only [derivWithin, fderivWithin_add_const]
theorem deriv_add_const (c : F) : deriv (fun y => f y + c) x = deriv f x := by
simp only [deriv, fderiv_add_const]
@[simp]
theorem deriv_add_const' (c : F) : (deriv fun y => f y + c) = deriv f :=
funext fun _ => deriv_add_const c
theorem hasDerivAtFilter_const_add_iff (c : F) :
HasDerivAtFilter (c + f ·) f' x L ↔ HasDerivAtFilter f f' x L :=
hasFDerivAtFilter_const_add_iff c
alias ⟨_, HasDerivAtFilter.const_add⟩ := hasDerivAtFilter_const_add_iff
@[simp]
theorem hasStrictDerivAt_const_add_iff (c : F) :
HasStrictDerivAt (c + f ·) f' x ↔ HasStrictDerivAt f f' x :=
hasStrictFDerivAt_const_add_iff c
alias ⟨_, HasStrictDerivAt.const_add⟩ := hasStrictDerivAt_const_add_iff
@[simp]
theorem hasDerivWithinAt_const_add_iff (c : F) :
HasDerivWithinAt (c + f ·) f' s x ↔ HasDerivWithinAt f f' s x :=
hasDerivAtFilter_const_add_iff c
alias ⟨_, HasDerivWithinAt.const_add⟩ := hasDerivWithinAt_const_add_iff
@[simp]
theorem hasDerivAt_const_add_iff (c : F) : HasDerivAt (c + f ·) f' x ↔ HasDerivAt f f' x :=
hasDerivAtFilter_const_add_iff c
alias ⟨_, HasDerivAt.const_add⟩ := hasDerivAt_const_add_iff
theorem derivWithin_const_add (c : F) :
derivWithin (c + f ·) s x = derivWithin f s x := by
simp only [derivWithin, fderivWithin_const_add]
@[simp]
theorem derivWithin_const_add_fun (c : F) :
derivWithin (c + f ·) = derivWithin f := by
ext
apply derivWithin_const_add
theorem deriv_const_add (c : F) : deriv (c + f ·) x = deriv f x := by
simp only [deriv, fderiv_const_add]
@[simp]
theorem deriv_const_add' (c : F) : (deriv (c + f ·)) = deriv f :=
funext fun _ => deriv_const_add c
lemma differentiableAt_comp_const_add {a b : 𝕜} :
DifferentiableAt 𝕜 (fun x ↦ f (b + x)) a ↔ DifferentiableAt 𝕜 f (b + a) := by
refine ⟨fun H ↦ ?_, fun H ↦ H.comp _ (differentiable_id.const_add _).differentiableAt⟩
convert DifferentiableAt.comp (b + a) (by simpa)
(differentiable_id.const_add (-b)).differentiableAt
ext
simp
lemma differentiableAt_comp_add_const {a b : 𝕜} :
DifferentiableAt 𝕜 (fun x ↦ f (x + b)) a ↔ DifferentiableAt 𝕜 f (a + b) := by
simpa [add_comm b] using differentiableAt_comp_const_add (f := f) (b := b)
lemma differentiableAt_iff_comp_const_add {a b : 𝕜} :
DifferentiableAt 𝕜 f a ↔ DifferentiableAt 𝕜 (fun x ↦ f (b + x)) (-b + a) := by
simp [differentiableAt_comp_const_add]
lemma differentiableAt_iff_comp_add_const {a b : 𝕜} :
DifferentiableAt 𝕜 f a ↔ DifferentiableAt 𝕜 (fun x ↦ f (x + b)) (a - b) := by
simp [differentiableAt_comp_add_const]
end Add
section Sum
/-! ### Derivative of a finite sum of functions -/
variable {ι : Type*} {u : Finset ι} {A : ι → 𝕜 → F} {A' : ι → F}
theorem HasDerivAtFilter.sum (h : ∀ i ∈ u, HasDerivAtFilter (A i) (A' i) x L) :
HasDerivAtFilter (fun y => ∑ i ∈ u, A i y) (∑ i ∈ u, A' i) x L := by
simpa [ContinuousLinearMap.sum_apply] using (HasFDerivAtFilter.sum h).hasDerivAtFilter
theorem HasStrictDerivAt.sum (h : ∀ i ∈ u, HasStrictDerivAt (A i) (A' i) x) :
HasStrictDerivAt (fun y => ∑ i ∈ u, A i y) (∑ i ∈ u, A' i) x := by
simpa [ContinuousLinearMap.sum_apply] using (HasStrictFDerivAt.sum h).hasStrictDerivAt
theorem HasDerivWithinAt.sum (h : ∀ i ∈ u, HasDerivWithinAt (A i) (A' i) s x) :
HasDerivWithinAt (fun y => ∑ i ∈ u, A i y) (∑ i ∈ u, A' i) s x :=
HasDerivAtFilter.sum h
theorem HasDerivAt.sum (h : ∀ i ∈ u, HasDerivAt (A i) (A' i) x) :
HasDerivAt (fun y => ∑ i ∈ u, A i y) (∑ i ∈ u, A' i) x :=
HasDerivAtFilter.sum h
theorem derivWithin_sum (h : ∀ i ∈ u, DifferentiableWithinAt 𝕜 (A i) s x) :
derivWithin (fun y => ∑ i ∈ u, A i y) s x = ∑ i ∈ u, derivWithin (A i) s x := by
by_cases hsx : UniqueDiffWithinAt 𝕜 s x
· exact (HasDerivWithinAt.sum fun i hi => (h i hi).hasDerivWithinAt).derivWithin hsx
· simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx]
@[simp]
theorem deriv_sum (h : ∀ i ∈ u, DifferentiableAt 𝕜 (A i) x) :
deriv (fun y => ∑ i ∈ u, A i y) x = ∑ i ∈ u, deriv (A i) x :=
(HasDerivAt.sum fun i hi => (h i hi).hasDerivAt).deriv
end Sum
section Neg
/-! ### Derivative of the negative of a function -/
nonrec theorem HasDerivAtFilter.neg (h : HasDerivAtFilter f f' x L) :
HasDerivAtFilter (fun x => -f x) (-f') x L := by simpa using h.neg.hasDerivAtFilter
nonrec theorem HasDerivWithinAt.neg (h : HasDerivWithinAt f f' s x) :
HasDerivWithinAt (fun x => -f x) (-f') s x :=
h.neg
nonrec theorem HasDerivAt.neg (h : HasDerivAt f f' x) : HasDerivAt (fun x => -f x) (-f') x :=
h.neg
nonrec theorem HasStrictDerivAt.neg (h : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun x => -f x) (-f') x := by simpa using h.neg.hasStrictDerivAt
theorem derivWithin.neg : derivWithin (fun y => -f y) s x = -derivWithin f s x := by
by_cases hsx : UniqueDiffWithinAt 𝕜 s x
· simp only [derivWithin, fderivWithin_neg hsx, ContinuousLinearMap.neg_apply]
· simp [derivWithin_zero_of_not_uniqueDiffWithinAt hsx]
theorem deriv.neg : deriv (fun y => -f y) x = -deriv f x := by
simp only [deriv, fderiv_neg, ContinuousLinearMap.neg_apply]
@[simp]
theorem deriv.neg' : (deriv fun y => -f y) = fun x => -deriv f x :=
funext fun _ => deriv.neg
end Neg
section Neg2
/-! ### Derivative of the negation function (i.e `Neg.neg`) -/
variable (s x L)
theorem hasDerivAtFilter_neg : HasDerivAtFilter Neg.neg (-1) x L :=
HasDerivAtFilter.neg <| hasDerivAtFilter_id _ _
theorem hasDerivWithinAt_neg : HasDerivWithinAt Neg.neg (-1) s x :=
hasDerivAtFilter_neg _ _
theorem hasDerivAt_neg : HasDerivAt Neg.neg (-1) x :=
hasDerivAtFilter_neg _ _
theorem hasDerivAt_neg' : HasDerivAt (fun x => -x) (-1) x :=
hasDerivAtFilter_neg _ _
theorem hasStrictDerivAt_neg : HasStrictDerivAt Neg.neg (-1) x :=
HasStrictDerivAt.neg <| hasStrictDerivAt_id _
theorem deriv_neg : deriv Neg.neg x = -1 :=
HasDerivAt.deriv (hasDerivAt_neg x)
@[simp]
theorem deriv_neg' : deriv (Neg.neg : 𝕜 → 𝕜) = fun _ => -1 :=
funext deriv_neg
@[simp]
theorem deriv_neg'' : deriv (fun x : 𝕜 => -x) x = -1 :=
deriv_neg x
theorem derivWithin_neg (hxs : UniqueDiffWithinAt 𝕜 s x) : derivWithin Neg.neg s x = -1 :=
(hasDerivWithinAt_neg x s).derivWithin hxs
theorem differentiable_neg : Differentiable 𝕜 (Neg.neg : 𝕜 → 𝕜) :=
Differentiable.neg differentiable_id
theorem differentiableOn_neg : DifferentiableOn 𝕜 (Neg.neg : 𝕜 → 𝕜) s :=
DifferentiableOn.neg differentiableOn_id
lemma differentiableAt_comp_neg {a : 𝕜} :
DifferentiableAt 𝕜 (fun x ↦ f (-x)) a ↔ DifferentiableAt 𝕜 f (-a) := by
refine ⟨fun H ↦ ?_, fun H ↦ H.comp a differentiable_neg.differentiableAt⟩
convert ((neg_neg a).symm ▸ H).comp (-a) differentiable_neg.differentiableAt
ext
simp only [Function.comp_apply, neg_neg]
lemma differentiableAt_iff_comp_neg {a : 𝕜} :
DifferentiableAt 𝕜 f a ↔ DifferentiableAt 𝕜 (fun x ↦ f (-x)) (-a) := by
simp_rw [← differentiableAt_comp_neg, neg_neg]
end Neg2
section Sub
/-! ### Derivative of the difference of two functions -/
theorem HasDerivAtFilter.sub (hf : HasDerivAtFilter f f' x L) (hg : HasDerivAtFilter g g' x L) :
HasDerivAtFilter (fun x => f x - g x) (f' - g') x L := by
simpa only [sub_eq_add_neg] using hf.add hg.neg
nonrec theorem HasDerivWithinAt.sub (hf : HasDerivWithinAt f f' s x)
(hg : HasDerivWithinAt g g' s x) : HasDerivWithinAt (fun x => f x - g x) (f' - g') s x :=
hf.sub hg
nonrec theorem HasDerivAt.sub (hf : HasDerivAt f f' x) (hg : HasDerivAt g g' x) :
HasDerivAt (fun x => f x - g x) (f' - g') x :=
hf.sub hg
theorem HasStrictDerivAt.sub (hf : HasStrictDerivAt f f' x) (hg : HasStrictDerivAt g g' x) :
HasStrictDerivAt (fun x => f x - g x) (f' - g') x := by
simpa only [sub_eq_add_neg] using hf.add hg.neg
theorem derivWithin_sub (hf : DifferentiableWithinAt 𝕜 f s x)
(hg : DifferentiableWithinAt 𝕜 g s x) :
derivWithin (fun y => f y - g y) s x = derivWithin f s x - derivWithin g s x := by
simp only [sub_eq_add_neg, derivWithin_add hf hg.neg, derivWithin.neg]
@[simp]
theorem deriv_sub (hf : DifferentiableAt 𝕜 f x) (hg : DifferentiableAt 𝕜 g x) :
deriv (fun y => f y - g y) x = deriv f x - deriv g x :=
(hf.hasDerivAt.sub hg.hasDerivAt).deriv
@[simp]
theorem hasDerivAtFilter_sub_const_iff (c : F) :
HasDerivAtFilter (fun x => f x - c) f' x L ↔ HasDerivAtFilter f f' x L :=
hasFDerivAtFilter_sub_const_iff c
alias ⟨_, HasDerivAtFilter.sub_const⟩ := hasDerivAtFilter_sub_const_iff
@[simp]
theorem hasDerivWithinAt_sub_const_iff (c : F) :
HasDerivWithinAt (f · - c) f' s x ↔ HasDerivWithinAt f f' s x :=
hasDerivAtFilter_sub_const_iff c
alias ⟨_, HasDerivWithinAt.sub_const⟩ := hasDerivWithinAt_sub_const_iff
@[simp]
theorem hasDerivAt_sub_const_iff (c : F) : HasDerivAt (f · - c) f' x ↔ HasDerivAt f f' x :=
hasDerivAtFilter_sub_const_iff c
alias ⟨_, HasDerivAt.sub_const⟩ := hasDerivAt_sub_const_iff
theorem derivWithin_sub_const (c : F) :
derivWithin (fun y => f y - c) s x = derivWithin f s x := by
simp only [derivWithin, fderivWithin_sub_const]
@[simp]
theorem derivWithin_sub_const_fun (c : F) : derivWithin (f · - c) = derivWithin f := by
ext
apply derivWithin_sub_const
theorem deriv_sub_const (c : F) : deriv (fun y => f y - c) x = deriv f x := by
simp only [deriv, fderiv_sub_const]
@[simp]
| Mathlib/Analysis/Calculus/Deriv/Add.lean | 353 | 355 | theorem deriv_sub_const_fun (c : F) : deriv (f · - c) = deriv f := by | ext
apply deriv_sub_const |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Bhavik Mehta, Stuart Presnell
-/
import Mathlib.Data.Nat.Factorial.Basic
import Mathlib.Order.Monotone.Defs
/-!
# Binomial coefficients
This file defines binomial coefficients and proves simple lemmas (i.e. those not
requiring more imports).
For the lemma that `n.choose k` counts the `k`-element-subsets of an `n`-element set,
see `Fintype.card_powersetCard` in `Mathlib.Data.Finset.Powerset`.
## Main definition and results
* `Nat.choose`: binomial coefficients, defined inductively
* `Nat.choose_eq_factorial_div_factorial`: a proof that `choose n k = n! / (k! * (n - k)!)`
* `Nat.choose_symm`: symmetry of binomial coefficients
* `Nat.choose_le_succ_of_lt_half_left`: `choose n k` is increasing for small values of `k`
* `Nat.choose_le_middle`: `choose n r` is maximised when `r` is `n/2`
* `Nat.descFactorial_eq_factorial_mul_choose`: Relates binomial coefficients to the descending
factorial. This is used to prove `Nat.choose_le_pow` and variants. We provide similar statements
for the ascending factorial.
* `Nat.multichoose`: whereas `choose` counts combinations, `multichoose` counts multicombinations.
The fact that this is indeed the correct counting function for multisets is proved in
`Sym.card_sym_eq_multichoose` in `Data.Sym.Card`.
* `Nat.multichoose_eq` : a proof that `multichoose n k = (n + k - 1).choose k`.
This is central to the "stars and bars" technique in informal mathematics, where we switch between
counting multisets of size `k` over an alphabet of size `n` to counting strings of `k` elements
("stars") separated by `n-1` dividers ("bars"). See `Data.Sym.Card` for more detail.
## Tags
binomial coefficient, combination, multicombination, stars and bars
-/
open Nat
namespace Nat
/-- `choose n k` is the number of `k`-element subsets in an `n`-element set. Also known as binomial
coefficients. For the fact that this is the number of `k`-element-subsets of an `n`-element
set, see `Fintype.card_powersetCard`. -/
def choose : ℕ → ℕ → ℕ
| _, 0 => 1
| 0, _ + 1 => 0
| n + 1, k + 1 => choose n k + choose n (k + 1)
@[simp]
theorem choose_zero_right (n : ℕ) : choose n 0 = 1 := by cases n <;> rfl
@[simp]
theorem choose_zero_succ (k : ℕ) : choose 0 (succ k) = 0 :=
rfl
theorem choose_succ_succ (n k : ℕ) : choose (succ n) (succ k) = choose n k + choose n (succ k) :=
rfl
theorem choose_succ_succ' (n k : ℕ) : choose (n + 1) (k + 1) = choose n k + choose n (k + 1) :=
rfl
theorem choose_succ_left (n k : ℕ) (hk : 0 < k) :
choose (n + 1) k = choose n (k - 1) + choose n k := by
obtain ⟨l, rfl⟩ : ∃ l, k = l + 1 := Nat.exists_eq_add_of_le' hk
rfl
theorem choose_succ_right (n k : ℕ) (hn : 0 < n) :
choose n (k + 1) = choose (n - 1) k + choose (n - 1) (k + 1) := by
obtain ⟨l, rfl⟩ : ∃ l, n = l + 1 := Nat.exists_eq_add_of_le' hn
rfl
theorem choose_eq_choose_pred_add {n k : ℕ} (hn : 0 < n) (hk : 0 < k) :
choose n k = choose (n - 1) (k - 1) + choose (n - 1) k := by
obtain ⟨l, rfl⟩ : ∃ l, k = l + 1 := Nat.exists_eq_add_of_le' hk
rw [choose_succ_right _ _ hn, Nat.add_one_sub_one]
theorem choose_eq_zero_of_lt : ∀ {n k}, n < k → choose n k = 0
| _, 0, hk => absurd hk (Nat.not_lt_zero _)
| 0, _ + 1, _ => choose_zero_succ _
| n + 1, k + 1, hk => by
have hnk : n < k := lt_of_succ_lt_succ hk
have hnk1 : n < k + 1 := lt_of_succ_lt hk
rw [choose_succ_succ, choose_eq_zero_of_lt hnk, choose_eq_zero_of_lt hnk1]
@[simp]
theorem choose_self (n : ℕ) : choose n n = 1 := by
induction n <;> simp [*, choose, choose_eq_zero_of_lt (lt_succ_self _)]
@[simp]
theorem choose_succ_self (n : ℕ) : choose n (succ n) = 0 :=
choose_eq_zero_of_lt (lt_succ_self _)
@[simp]
lemma choose_one_right (n : ℕ) : choose n 1 = n := by induction n <;> simp [*, choose, Nat.add_comm]
-- The `n+1`-st triangle number is `n` more than the `n`-th triangle number
theorem triangle_succ (n : ℕ) : (n + 1) * (n + 1 - 1) / 2 = n * (n - 1) / 2 + n := by
rw [← add_mul_div_left, Nat.mul_comm 2 n, ← Nat.mul_add, Nat.add_sub_cancel, Nat.mul_comm]
cases n <;> rfl; apply zero_lt_succ
/-- `choose n 2` is the `n`-th triangle number. -/
| Mathlib/Data/Nat/Choose/Basic.lean | 106 | 109 | theorem choose_two_right (n : ℕ) : choose n 2 = n * (n - 1) / 2 := by | induction' n with n ih
· simp
· rw [triangle_succ n, choose, ih] |
/-
Copyright (c) 2018 Patrick Massot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Patrick Massot, Johannes Hölzl, Yaël Dillies
-/
import Mathlib.Analysis.Normed.Group.Continuity
import Mathlib.Topology.Algebra.IsUniformGroup.Basic
import Mathlib.Topology.MetricSpace.Algebra
import Mathlib.Topology.MetricSpace.IsometricSMul
/-!
# Normed groups are uniform groups
This file proves lipschitzness of normed group operations and shows that normed groups are uniform
groups.
-/
variable {𝓕 E F : Type*}
open Filter Function Metric Bornology
open scoped ENNReal NNReal Uniformity Pointwise Topology
section SeminormedGroup
variable [SeminormedGroup E] [SeminormedGroup F] {s : Set E} {a b : E} {r : ℝ}
@[to_additive]
instance NormedGroup.to_isIsometricSMul_right : IsIsometricSMul Eᵐᵒᵖ E :=
⟨fun a => Isometry.of_dist_eq fun b c => by simp [dist_eq_norm_div]⟩
@[to_additive]
theorem Isometry.norm_map_of_map_one {f : E → F} (hi : Isometry f) (h₁ : f 1 = 1) (x : E) :
‖f x‖ = ‖x‖ := by rw [← dist_one_right, ← h₁, hi.dist_eq, dist_one_right]
@[to_additive (attr := simp)]
| Mathlib/Analysis/Normed/Group/Uniform.lean | 35 | 36 | theorem dist_mul_self_right (a b : E) : dist b (a * b) = ‖a‖ := by | rw [← dist_one_left, ← dist_mul_right 1 a b, one_mul] |
/-
Copyright (c) 2021 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Algebra.GroupWithZero.Indicator
import Mathlib.Topology.Piecewise
import Mathlib.Topology.Instances.ENNReal.Lemmas
/-!
# Semicontinuous maps
A function `f` from a topological space `α` to an ordered space `β` is lower semicontinuous at a
point `x` if, for any `y < f x`, for any `x'` close enough to `x`, one has `f x' > y`. In other
words, `f` can jump up, but it can not jump down.
Upper semicontinuous functions are defined similarly.
This file introduces these notions, and a basic API around them mimicking the API for continuous
functions.
## Main definitions and results
We introduce 4 definitions related to lower semicontinuity:
* `LowerSemicontinuousWithinAt f s x`
* `LowerSemicontinuousAt f x`
* `LowerSemicontinuousOn f s`
* `LowerSemicontinuous f`
We build a basic API using dot notation around these notions, and we prove that
* constant functions are lower semicontinuous;
* `indicator s (fun _ ↦ y)` is lower semicontinuous when `s` is open and `0 ≤ y`,
or when `s` is closed and `y ≤ 0`;
* continuous functions are lower semicontinuous;
* left composition with a continuous monotone functions maps lower semicontinuous functions to lower
semicontinuous functions. If the function is anti-monotone, it instead maps lower semicontinuous
functions to upper semicontinuous functions;
* right composition with continuous functions preserves lower and upper semicontinuity;
* a sum of two (or finitely many) lower semicontinuous functions is lower semicontinuous;
* a supremum of a family of lower semicontinuous functions is lower semicontinuous;
* An infinite sum of `ℝ≥0∞`-valued lower semicontinuous functions is lower semicontinuous.
Similar results are stated and proved for upper semicontinuity.
We also prove that a function is continuous if and only if it is both lower and upper
semicontinuous.
We have some equivalent definitions of lower- and upper-semicontinuity (under certain
restrictions on the order on the codomain):
* `lowerSemicontinuous_iff_isOpen_preimage` in a linear order;
* `lowerSemicontinuous_iff_isClosed_preimage` in a linear order;
* `lowerSemicontinuousAt_iff_le_liminf` in a dense complete linear order;
* `lowerSemicontinuous_iff_isClosed_epigraph` in a dense complete linear order with the order
topology.
## Implementation details
All the nontrivial results for upper semicontinuous functions are deduced from the corresponding
ones for lower semicontinuous functions using `OrderDual`.
## References
* <https://en.wikipedia.org/wiki/Closed_convex_function>
* <https://en.wikipedia.org/wiki/Semi-continuity>
-/
open Topology ENNReal
open Set Function Filter
variable {α : Type*} [TopologicalSpace α] {β : Type*} [Preorder β] {f g : α → β} {x : α}
{s t : Set α} {y z : β}
/-! ### Main definitions -/
/-- A real function `f` is lower semicontinuous at `x` within a set `s` if, for any `ε > 0`, for all
`x'` close enough to `x` in `s`, then `f x'` is at least `f x - ε`. We formulate this in a general
preordered space, using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuousWithinAt (f : α → β) (s : Set α) (x : α) :=
∀ y < f x, ∀ᶠ x' in 𝓝[s] x, y < f x'
/-- A real function `f` is lower semicontinuous on a set `s` if, for any `ε > 0`, for any `x ∈ s`,
for all `x'` close enough to `x` in `s`, then `f x'` is at least `f x - ε`. We formulate this in
a general preordered space, using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuousOn (f : α → β) (s : Set α) :=
∀ x ∈ s, LowerSemicontinuousWithinAt f s x
/-- A real function `f` is lower semicontinuous at `x` if, for any `ε > 0`, for all `x'` close
enough to `x`, then `f x'` is at least `f x - ε`. We formulate this in a general preordered space,
using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuousAt (f : α → β) (x : α) :=
∀ y < f x, ∀ᶠ x' in 𝓝 x, y < f x'
/-- A real function `f` is lower semicontinuous if, for any `ε > 0`, for any `x`, for all `x'` close
enough to `x`, then `f x'` is at least `f x - ε`. We formulate this in a general preordered space,
using an arbitrary `y < f x` instead of `f x - ε`. -/
def LowerSemicontinuous (f : α → β) :=
∀ x, LowerSemicontinuousAt f x
/-- A real function `f` is upper semicontinuous at `x` within a set `s` if, for any `ε > 0`, for all
`x'` close enough to `x` in `s`, then `f x'` is at most `f x + ε`. We formulate this in a general
preordered space, using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuousWithinAt (f : α → β) (s : Set α) (x : α) :=
∀ y, f x < y → ∀ᶠ x' in 𝓝[s] x, f x' < y
/-- A real function `f` is upper semicontinuous on a set `s` if, for any `ε > 0`, for any `x ∈ s`,
for all `x'` close enough to `x` in `s`, then `f x'` is at most `f x + ε`. We formulate this in a
general preordered space, using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuousOn (f : α → β) (s : Set α) :=
∀ x ∈ s, UpperSemicontinuousWithinAt f s x
/-- A real function `f` is upper semicontinuous at `x` if, for any `ε > 0`, for all `x'` close
enough to `x`, then `f x'` is at most `f x + ε`. We formulate this in a general preordered space,
using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuousAt (f : α → β) (x : α) :=
∀ y, f x < y → ∀ᶠ x' in 𝓝 x, f x' < y
/-- A real function `f` is upper semicontinuous if, for any `ε > 0`, for any `x`, for all `x'`
close enough to `x`, then `f x'` is at most `f x + ε`. We formulate this in a general preordered
space, using an arbitrary `y > f x` instead of `f x + ε`. -/
def UpperSemicontinuous (f : α → β) :=
∀ x, UpperSemicontinuousAt f x
/-!
### Lower semicontinuous functions
-/
/-! #### Basic dot notation interface for lower semicontinuity -/
theorem LowerSemicontinuousWithinAt.mono (h : LowerSemicontinuousWithinAt f s x) (hst : t ⊆ s) :
LowerSemicontinuousWithinAt f t x := fun y hy =>
Filter.Eventually.filter_mono (nhdsWithin_mono _ hst) (h y hy)
theorem lowerSemicontinuousWithinAt_univ_iff :
LowerSemicontinuousWithinAt f univ x ↔ LowerSemicontinuousAt f x := by
simp [LowerSemicontinuousWithinAt, LowerSemicontinuousAt, nhdsWithin_univ]
theorem LowerSemicontinuousAt.lowerSemicontinuousWithinAt (s : Set α)
(h : LowerSemicontinuousAt f x) : LowerSemicontinuousWithinAt f s x := fun y hy =>
Filter.Eventually.filter_mono nhdsWithin_le_nhds (h y hy)
theorem LowerSemicontinuousOn.lowerSemicontinuousWithinAt (h : LowerSemicontinuousOn f s)
(hx : x ∈ s) : LowerSemicontinuousWithinAt f s x :=
h x hx
theorem LowerSemicontinuousOn.mono (h : LowerSemicontinuousOn f s) (hst : t ⊆ s) :
LowerSemicontinuousOn f t := fun x hx => (h x (hst hx)).mono hst
theorem lowerSemicontinuousOn_univ_iff : LowerSemicontinuousOn f univ ↔ LowerSemicontinuous f := by
simp [LowerSemicontinuousOn, LowerSemicontinuous, lowerSemicontinuousWithinAt_univ_iff]
theorem LowerSemicontinuous.lowerSemicontinuousAt (h : LowerSemicontinuous f) (x : α) :
LowerSemicontinuousAt f x :=
h x
theorem LowerSemicontinuous.lowerSemicontinuousWithinAt (h : LowerSemicontinuous f) (s : Set α)
(x : α) : LowerSemicontinuousWithinAt f s x :=
(h x).lowerSemicontinuousWithinAt s
theorem LowerSemicontinuous.lowerSemicontinuousOn (h : LowerSemicontinuous f) (s : Set α) :
LowerSemicontinuousOn f s := fun x _hx => h.lowerSemicontinuousWithinAt s x
/-! #### Constants -/
theorem lowerSemicontinuousWithinAt_const : LowerSemicontinuousWithinAt (fun _x => z) s x :=
fun _y hy => Filter.Eventually.of_forall fun _x => hy
theorem lowerSemicontinuousAt_const : LowerSemicontinuousAt (fun _x => z) x := fun _y hy =>
Filter.Eventually.of_forall fun _x => hy
theorem lowerSemicontinuousOn_const : LowerSemicontinuousOn (fun _x => z) s := fun _x _hx =>
lowerSemicontinuousWithinAt_const
theorem lowerSemicontinuous_const : LowerSemicontinuous fun _x : α => z := fun _x =>
lowerSemicontinuousAt_const
/-! #### Indicators -/
section
variable [Zero β]
theorem IsOpen.lowerSemicontinuous_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuous (indicator s fun _x => y) := by
intro x z hz
by_cases h : x ∈ s <;> simp [h] at hz
· filter_upwards [hs.mem_nhds h]
simp +contextual [hz]
· refine Filter.Eventually.of_forall fun x' => ?_
by_cases h' : x' ∈ s <;> simp [h', hz.trans_le hy, hz]
theorem IsOpen.lowerSemicontinuousOn_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuousOn (indicator s fun _x => y) t :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousOn t
theorem IsOpen.lowerSemicontinuousAt_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuousAt (indicator s fun _x => y) x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousAt x
theorem IsOpen.lowerSemicontinuousWithinAt_indicator (hs : IsOpen s) (hy : 0 ≤ y) :
LowerSemicontinuousWithinAt (indicator s fun _x => y) t x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousWithinAt t x
theorem IsClosed.lowerSemicontinuous_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuous (indicator s fun _x => y) := by
intro x z hz
by_cases h : x ∈ s <;> simp [h] at hz
· refine Filter.Eventually.of_forall fun x' => ?_
by_cases h' : x' ∈ s <;> simp [h', hz, hz.trans_le hy]
· filter_upwards [hs.isOpen_compl.mem_nhds h]
simp +contextual [hz]
theorem IsClosed.lowerSemicontinuousOn_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuousOn (indicator s fun _x => y) t :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousOn t
theorem IsClosed.lowerSemicontinuousAt_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuousAt (indicator s fun _x => y) x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousAt x
theorem IsClosed.lowerSemicontinuousWithinAt_indicator (hs : IsClosed s) (hy : y ≤ 0) :
LowerSemicontinuousWithinAt (indicator s fun _x => y) t x :=
(hs.lowerSemicontinuous_indicator hy).lowerSemicontinuousWithinAt t x
end
/-! #### Relationship with continuity -/
theorem lowerSemicontinuous_iff_isOpen_preimage :
LowerSemicontinuous f ↔ ∀ y, IsOpen (f ⁻¹' Ioi y) :=
⟨fun H y => isOpen_iff_mem_nhds.2 fun x hx => H x y hx, fun H _x y y_lt =>
IsOpen.mem_nhds (H y) y_lt⟩
theorem LowerSemicontinuous.isOpen_preimage (hf : LowerSemicontinuous f) (y : β) :
IsOpen (f ⁻¹' Ioi y) :=
lowerSemicontinuous_iff_isOpen_preimage.1 hf y
section
variable {γ : Type*} [LinearOrder γ]
theorem lowerSemicontinuous_iff_isClosed_preimage {f : α → γ} :
LowerSemicontinuous f ↔ ∀ y, IsClosed (f ⁻¹' Iic y) := by
rw [lowerSemicontinuous_iff_isOpen_preimage]
simp only [← isOpen_compl_iff, ← preimage_compl, compl_Iic]
theorem LowerSemicontinuous.isClosed_preimage {f : α → γ} (hf : LowerSemicontinuous f) (y : γ) :
IsClosed (f ⁻¹' Iic y) :=
lowerSemicontinuous_iff_isClosed_preimage.1 hf y
variable [TopologicalSpace γ] [OrderTopology γ]
theorem ContinuousWithinAt.lowerSemicontinuousWithinAt {f : α → γ} (h : ContinuousWithinAt f s x) :
LowerSemicontinuousWithinAt f s x := fun _y hy => h (Ioi_mem_nhds hy)
theorem ContinuousAt.lowerSemicontinuousAt {f : α → γ} (h : ContinuousAt f x) :
LowerSemicontinuousAt f x := fun _y hy => h (Ioi_mem_nhds hy)
theorem ContinuousOn.lowerSemicontinuousOn {f : α → γ} (h : ContinuousOn f s) :
LowerSemicontinuousOn f s := fun x hx => (h x hx).lowerSemicontinuousWithinAt
theorem Continuous.lowerSemicontinuous {f : α → γ} (h : Continuous f) : LowerSemicontinuous f :=
fun _x => h.continuousAt.lowerSemicontinuousAt
end
/-! #### Equivalent definitions -/
section
variable {γ : Type*} [CompleteLinearOrder γ] [DenselyOrdered γ]
theorem lowerSemicontinuousWithinAt_iff_le_liminf {f : α → γ} :
LowerSemicontinuousWithinAt f s x ↔ f x ≤ liminf f (𝓝[s] x) := by
constructor
· intro hf; unfold LowerSemicontinuousWithinAt at hf
contrapose! hf
obtain ⟨y, lty, ylt⟩ := exists_between hf; use y
exact ⟨ylt, fun h => lty.not_le
(le_liminf_of_le (by isBoundedDefault) (h.mono fun _ hx => le_of_lt hx))⟩
exact fun hf y ylt => eventually_lt_of_lt_liminf (ylt.trans_le hf)
alias ⟨LowerSemicontinuousWithinAt.le_liminf, _⟩ := lowerSemicontinuousWithinAt_iff_le_liminf
theorem lowerSemicontinuousAt_iff_le_liminf {f : α → γ} :
LowerSemicontinuousAt f x ↔ f x ≤ liminf f (𝓝 x) := by
rw [← lowerSemicontinuousWithinAt_univ_iff, lowerSemicontinuousWithinAt_iff_le_liminf,
← nhdsWithin_univ]
alias ⟨LowerSemicontinuousAt.le_liminf, _⟩ := lowerSemicontinuousAt_iff_le_liminf
theorem lowerSemicontinuous_iff_le_liminf {f : α → γ} :
LowerSemicontinuous f ↔ ∀ x, f x ≤ liminf f (𝓝 x) := by
simp only [← lowerSemicontinuousAt_iff_le_liminf, LowerSemicontinuous]
alias ⟨LowerSemicontinuous.le_liminf, _⟩ := lowerSemicontinuous_iff_le_liminf
theorem lowerSemicontinuousOn_iff_le_liminf {f : α → γ} :
LowerSemicontinuousOn f s ↔ ∀ x ∈ s, f x ≤ liminf f (𝓝[s] x) := by
simp only [← lowerSemicontinuousWithinAt_iff_le_liminf, LowerSemicontinuousOn]
alias ⟨LowerSemicontinuousOn.le_liminf, _⟩ := lowerSemicontinuousOn_iff_le_liminf
variable [TopologicalSpace γ] [OrderTopology γ]
theorem lowerSemicontinuous_iff_isClosed_epigraph {f : α → γ} :
LowerSemicontinuous f ↔ IsClosed {p : α × γ | f p.1 ≤ p.2} := by
constructor
· rw [lowerSemicontinuous_iff_le_liminf, isClosed_iff_forall_filter]
rintro hf ⟨x, y⟩ F F_ne h h'
rw [nhds_prod_eq, le_prod] at h'
calc f x ≤ liminf f (𝓝 x) := hf x
_ ≤ liminf f (map Prod.fst F) := liminf_le_liminf_of_le h'.1
_ = liminf (f ∘ Prod.fst) F := (Filter.liminf_comp _ _ _).symm
_ ≤ liminf Prod.snd F := liminf_le_liminf <| by
simpa using (eventually_principal.2 fun (_ : α × γ) ↦ id).filter_mono h
_ = y := h'.2.liminf_eq
· rw [lowerSemicontinuous_iff_isClosed_preimage]
exact fun hf y ↦ hf.preimage (.prodMk_left y)
alias ⟨LowerSemicontinuous.isClosed_epigraph, _⟩ := lowerSemicontinuous_iff_isClosed_epigraph
end
/-! ### Composition -/
section
variable {γ : Type*} [LinearOrder γ] [TopologicalSpace γ] [OrderTopology γ]
variable {δ : Type*} [LinearOrder δ] [TopologicalSpace δ] [OrderTopology δ]
variable {ι : Type*} [TopologicalSpace ι]
theorem ContinuousAt.comp_lowerSemicontinuousWithinAt {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : LowerSemicontinuousWithinAt f s x) (gmon : Monotone g) :
LowerSemicontinuousWithinAt (g ∘ f) s x := by
intro y hy
by_cases h : ∃ l, l < f x
· obtain ⟨z, zlt, hz⟩ : ∃ z < f x, Ioc z (f x) ⊆ g ⁻¹' Ioi y :=
exists_Ioc_subset_of_mem_nhds (hg (Ioi_mem_nhds hy)) h
filter_upwards [hf z zlt] with a ha
calc
y < g (min (f x) (f a)) := hz (by simp [zlt, ha, le_refl])
_ ≤ g (f a) := gmon (min_le_right _ _)
· simp only [not_exists, not_lt] at h
exact Filter.Eventually.of_forall fun a => hy.trans_le (gmon (h (f a)))
theorem ContinuousAt.comp_lowerSemicontinuousAt {g : γ → δ} {f : α → γ} (hg : ContinuousAt g (f x))
(hf : LowerSemicontinuousAt f x) (gmon : Monotone g) : LowerSemicontinuousAt (g ∘ f) x := by
simp only [← lowerSemicontinuousWithinAt_univ_iff] at hf ⊢
exact hg.comp_lowerSemicontinuousWithinAt hf gmon
theorem Continuous.comp_lowerSemicontinuousOn {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuousOn f s) (gmon : Monotone g) : LowerSemicontinuousOn (g ∘ f) s :=
fun x hx => hg.continuousAt.comp_lowerSemicontinuousWithinAt (hf x hx) gmon
theorem Continuous.comp_lowerSemicontinuous {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuous f) (gmon : Monotone g) : LowerSemicontinuous (g ∘ f) := fun x =>
hg.continuousAt.comp_lowerSemicontinuousAt (hf x) gmon
theorem ContinuousAt.comp_lowerSemicontinuousWithinAt_antitone {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : LowerSemicontinuousWithinAt f s x) (gmon : Antitone g) :
UpperSemicontinuousWithinAt (g ∘ f) s x :=
@ContinuousAt.comp_lowerSemicontinuousWithinAt α _ x s γ _ _ _ δᵒᵈ _ _ _ g f hg hf gmon
theorem ContinuousAt.comp_lowerSemicontinuousAt_antitone {g : γ → δ} {f : α → γ}
(hg : ContinuousAt g (f x)) (hf : LowerSemicontinuousAt f x) (gmon : Antitone g) :
UpperSemicontinuousAt (g ∘ f) x :=
@ContinuousAt.comp_lowerSemicontinuousAt α _ x γ _ _ _ δᵒᵈ _ _ _ g f hg hf gmon
theorem Continuous.comp_lowerSemicontinuousOn_antitone {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuousOn f s) (gmon : Antitone g) : UpperSemicontinuousOn (g ∘ f) s :=
fun x hx => hg.continuousAt.comp_lowerSemicontinuousWithinAt_antitone (hf x hx) gmon
theorem Continuous.comp_lowerSemicontinuous_antitone {g : γ → δ} {f : α → γ} (hg : Continuous g)
(hf : LowerSemicontinuous f) (gmon : Antitone g) : UpperSemicontinuous (g ∘ f) := fun x =>
hg.continuousAt.comp_lowerSemicontinuousAt_antitone (hf x) gmon
theorem LowerSemicontinuousAt.comp_continuousAt {f : α → β} {g : ι → α} {x : ι}
(hf : LowerSemicontinuousAt f (g x)) (hg : ContinuousAt g x) :
LowerSemicontinuousAt (fun x ↦ f (g x)) x :=
fun _ lt ↦ hg.eventually (hf _ lt)
theorem LowerSemicontinuousAt.comp_continuousAt_of_eq {f : α → β} {g : ι → α} {y : α} {x : ι}
(hf : LowerSemicontinuousAt f y) (hg : ContinuousAt g x) (hy : g x = y) :
LowerSemicontinuousAt (fun x ↦ f (g x)) x := by
rw [← hy] at hf
exact comp_continuousAt hf hg
theorem LowerSemicontinuous.comp_continuous {f : α → β} {g : ι → α}
(hf : LowerSemicontinuous f) (hg : Continuous g) : LowerSemicontinuous fun x ↦ f (g x) :=
fun x ↦ (hf (g x)).comp_continuousAt hg.continuousAt
end
/-! #### Addition -/
section
variable {ι : Type*} {γ : Type*} [AddCommMonoid γ] [LinearOrder γ] [IsOrderedAddMonoid γ]
[TopologicalSpace γ] [OrderTopology γ]
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuousWithinAt.add' {f g : α → γ} (hf : LowerSemicontinuousWithinAt f s x)
(hg : LowerSemicontinuousWithinAt g s x)
(hcont : ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuousWithinAt (fun z => f z + g z) s x := by
intro y hy
obtain ⟨u, v, u_open, xu, v_open, xv, h⟩ :
∃ u v : Set γ,
IsOpen u ∧ f x ∈ u ∧ IsOpen v ∧ g x ∈ v ∧ u ×ˢ v ⊆ { p : γ × γ | y < p.fst + p.snd } :=
mem_nhds_prod_iff'.1 (hcont (isOpen_Ioi.mem_nhds hy))
by_cases hx₁ : ∃ l, l < f x
· obtain ⟨z₁, z₁lt, h₁⟩ : ∃ z₁ < f x, Ioc z₁ (f x) ⊆ u :=
exists_Ioc_subset_of_mem_nhds (u_open.mem_nhds xu) hx₁
by_cases hx₂ : ∃ l, l < g x
· obtain ⟨z₂, z₂lt, h₂⟩ : ∃ z₂ < g x, Ioc z₂ (g x) ⊆ v :=
exists_Ioc_subset_of_mem_nhds (v_open.mem_nhds xv) hx₂
filter_upwards [hf z₁ z₁lt, hg z₂ z₂lt] with z h₁z h₂z
have A1 : min (f z) (f x) ∈ u := by
by_cases H : f z ≤ f x
· simpa [H] using h₁ ⟨h₁z, H⟩
· simpa [le_of_not_le H]
have A2 : min (g z) (g x) ∈ v := by
by_cases H : g z ≤ g x
· simpa [H] using h₂ ⟨h₂z, H⟩
· simpa [le_of_not_le H]
have : (min (f z) (f x), min (g z) (g x)) ∈ u ×ˢ v := ⟨A1, A2⟩
calc
y < min (f z) (f x) + min (g z) (g x) := h this
_ ≤ f z + g z := add_le_add (min_le_left _ _) (min_le_left _ _)
· simp only [not_exists, not_lt] at hx₂
filter_upwards [hf z₁ z₁lt] with z h₁z
have A1 : min (f z) (f x) ∈ u := by
by_cases H : f z ≤ f x
· simpa [H] using h₁ ⟨h₁z, H⟩
· simpa [le_of_not_le H]
have : (min (f z) (f x), g x) ∈ u ×ˢ v := ⟨A1, xv⟩
calc
y < min (f z) (f x) + g x := h this
_ ≤ f z + g z := add_le_add (min_le_left _ _) (hx₂ (g z))
· simp only [not_exists, not_lt] at hx₁
by_cases hx₂ : ∃ l, l < g x
· obtain ⟨z₂, z₂lt, h₂⟩ : ∃ z₂ < g x, Ioc z₂ (g x) ⊆ v :=
exists_Ioc_subset_of_mem_nhds (v_open.mem_nhds xv) hx₂
filter_upwards [hg z₂ z₂lt] with z h₂z
have A2 : min (g z) (g x) ∈ v := by
by_cases H : g z ≤ g x
· simpa [H] using h₂ ⟨h₂z, H⟩
· simpa [le_of_not_le H] using h₂ ⟨z₂lt, le_rfl⟩
have : (f x, min (g z) (g x)) ∈ u ×ˢ v := ⟨xu, A2⟩
calc
y < f x + min (g z) (g x) := h this
_ ≤ f z + g z := add_le_add (hx₁ (f z)) (min_le_left _ _)
· simp only [not_exists, not_lt] at hx₁ hx₂
apply Filter.Eventually.of_forall
intro z
have : (f x, g x) ∈ u ×ˢ v := ⟨xu, xv⟩
calc
y < f x + g x := h this
_ ≤ f z + g z := add_le_add (hx₁ (f z)) (hx₂ (g z))
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuousAt.add' {f g : α → γ} (hf : LowerSemicontinuousAt f x)
(hg : LowerSemicontinuousAt g x)
(hcont : ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuousAt (fun z => f z + g z) x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
exact hf.add' hg hcont
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuousOn.add' {f g : α → γ} (hf : LowerSemicontinuousOn f s)
(hg : LowerSemicontinuousOn g s)
(hcont : ∀ x ∈ s, ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuousOn (fun z => f z + g z) s := fun x hx =>
(hf x hx).add' (hg x hx) (hcont x hx)
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with an
explicit continuity assumption on addition, for application to `EReal`. The unprimed version of
the lemma uses `[ContinuousAdd]`. -/
theorem LowerSemicontinuous.add' {f g : α → γ} (hf : LowerSemicontinuous f)
(hg : LowerSemicontinuous g)
(hcont : ∀ x, ContinuousAt (fun p : γ × γ => p.1 + p.2) (f x, g x)) :
LowerSemicontinuous fun z => f z + g z := fun x => (hf x).add' (hg x) (hcont x)
variable [ContinuousAdd γ]
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuousWithinAt.add {f g : α → γ} (hf : LowerSemicontinuousWithinAt f s x)
(hg : LowerSemicontinuousWithinAt g s x) :
LowerSemicontinuousWithinAt (fun z => f z + g z) s x :=
hf.add' hg continuous_add.continuousAt
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuousAt.add {f g : α → γ} (hf : LowerSemicontinuousAt f x)
(hg : LowerSemicontinuousAt g x) : LowerSemicontinuousAt (fun z => f z + g z) x :=
hf.add' hg continuous_add.continuousAt
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuousOn.add {f g : α → γ} (hf : LowerSemicontinuousOn f s)
(hg : LowerSemicontinuousOn g s) : LowerSemicontinuousOn (fun z => f z + g z) s :=
hf.add' hg fun _x _hx => continuous_add.continuousAt
/-- The sum of two lower semicontinuous functions is lower semicontinuous. Formulated with
`[ContinuousAdd]`. The primed version of the lemma uses an explicit continuity assumption on
addition, for application to `EReal`. -/
theorem LowerSemicontinuous.add {f g : α → γ} (hf : LowerSemicontinuous f)
(hg : LowerSemicontinuous g) : LowerSemicontinuous fun z => f z + g z :=
hf.add' hg fun _x => continuous_add.continuousAt
theorem lowerSemicontinuousWithinAt_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun z => ∑ i ∈ a, f i z) s x := by
classical
induction a using Finset.induction_on with
| empty => exact lowerSemicontinuousWithinAt_const
| insert _ _ ia IH =>
simp only [ia, Finset.sum_insert, not_false_iff]
exact
LowerSemicontinuousWithinAt.add (ha _ (Finset.mem_insert_self ..))
(IH fun j ja => ha j (Finset.mem_insert_of_mem ja))
theorem lowerSemicontinuousAt_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun z => ∑ i ∈ a, f i z) x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
exact lowerSemicontinuousWithinAt_sum ha
theorem lowerSemicontinuousOn_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun z => ∑ i ∈ a, f i z) s := fun x hx =>
lowerSemicontinuousWithinAt_sum fun i hi => ha i hi x hx
theorem lowerSemicontinuous_sum {f : ι → α → γ} {a : Finset ι}
(ha : ∀ i ∈ a, LowerSemicontinuous (f i)) : LowerSemicontinuous fun z => ∑ i ∈ a, f i z :=
fun x => lowerSemicontinuousAt_sum fun i hi => ha i hi x
end
/-! #### Supremum -/
section
variable {ι : Sort*} {δ δ' : Type*} [CompleteLinearOrder δ] [ConditionallyCompleteLinearOrder δ']
theorem lowerSemicontinuousWithinAt_ciSup {f : ι → α → δ'}
(bdd : ∀ᶠ y in 𝓝[s] x, BddAbove (range fun i => f i y))
(h : ∀ i, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun x' => ⨆ i, f i x') s x := by
cases isEmpty_or_nonempty ι
· simpa only [iSup_of_empty'] using lowerSemicontinuousWithinAt_const
· intro y hy
rcases exists_lt_of_lt_ciSup hy with ⟨i, hi⟩
filter_upwards [h i y hi, bdd] with y hy hy' using hy.trans_le (le_ciSup hy' i)
theorem lowerSemicontinuousWithinAt_iSup {f : ι → α → δ}
(h : ∀ i, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun x' => ⨆ i, f i x') s x :=
lowerSemicontinuousWithinAt_ciSup (by simp) h
theorem lowerSemicontinuousWithinAt_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuousWithinAt (f i hi) s x) :
LowerSemicontinuousWithinAt (fun x' => ⨆ (i) (hi), f i hi x') s x :=
lowerSemicontinuousWithinAt_iSup fun i => lowerSemicontinuousWithinAt_iSup fun hi => h i hi
theorem lowerSemicontinuousAt_ciSup {f : ι → α → δ'}
(bdd : ∀ᶠ y in 𝓝 x, BddAbove (range fun i => f i y)) (h : ∀ i, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun x' => ⨆ i, f i x') x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
rw [← nhdsWithin_univ] at bdd
exact lowerSemicontinuousWithinAt_ciSup bdd h
theorem lowerSemicontinuousAt_iSup {f : ι → α → δ} (h : ∀ i, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun x' => ⨆ i, f i x') x :=
lowerSemicontinuousAt_ciSup (by simp) h
theorem lowerSemicontinuousAt_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuousAt (f i hi) x) :
LowerSemicontinuousAt (fun x' => ⨆ (i) (hi), f i hi x') x :=
lowerSemicontinuousAt_iSup fun i => lowerSemicontinuousAt_iSup fun hi => h i hi
theorem lowerSemicontinuousOn_ciSup {f : ι → α → δ'}
(bdd : ∀ x ∈ s, BddAbove (range fun i => f i x)) (h : ∀ i, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun x' => ⨆ i, f i x') s := fun x hx =>
lowerSemicontinuousWithinAt_ciSup (eventually_nhdsWithin_of_forall bdd) fun i => h i x hx
theorem lowerSemicontinuousOn_iSup {f : ι → α → δ} (h : ∀ i, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun x' => ⨆ i, f i x') s :=
lowerSemicontinuousOn_ciSup (by simp) h
theorem lowerSemicontinuousOn_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuousOn (f i hi) s) :
LowerSemicontinuousOn (fun x' => ⨆ (i) (hi), f i hi x') s :=
lowerSemicontinuousOn_iSup fun i => lowerSemicontinuousOn_iSup fun hi => h i hi
theorem lowerSemicontinuous_ciSup {f : ι → α → δ'} (bdd : ∀ x, BddAbove (range fun i => f i x))
(h : ∀ i, LowerSemicontinuous (f i)) : LowerSemicontinuous fun x' => ⨆ i, f i x' := fun x =>
lowerSemicontinuousAt_ciSup (Eventually.of_forall bdd) fun i => h i x
theorem lowerSemicontinuous_iSup {f : ι → α → δ} (h : ∀ i, LowerSemicontinuous (f i)) :
LowerSemicontinuous fun x' => ⨆ i, f i x' :=
lowerSemicontinuous_ciSup (by simp) h
theorem lowerSemicontinuous_biSup {p : ι → Prop} {f : ∀ i, p i → α → δ}
(h : ∀ i hi, LowerSemicontinuous (f i hi)) :
LowerSemicontinuous fun x' => ⨆ (i) (hi), f i hi x' :=
lowerSemicontinuous_iSup fun i => lowerSemicontinuous_iSup fun hi => h i hi
end
/-! #### Infinite sums -/
section
variable {ι : Type*}
theorem lowerSemicontinuousWithinAt_tsum {f : ι → α → ℝ≥0∞}
(h : ∀ i, LowerSemicontinuousWithinAt (f i) s x) :
LowerSemicontinuousWithinAt (fun x' => ∑' i, f i x') s x := by
simp_rw [ENNReal.tsum_eq_iSup_sum]
refine lowerSemicontinuousWithinAt_iSup fun b => ?_
exact lowerSemicontinuousWithinAt_sum fun i _hi => h i
theorem lowerSemicontinuousAt_tsum {f : ι → α → ℝ≥0∞} (h : ∀ i, LowerSemicontinuousAt (f i) x) :
LowerSemicontinuousAt (fun x' => ∑' i, f i x') x := by
simp_rw [← lowerSemicontinuousWithinAt_univ_iff] at *
exact lowerSemicontinuousWithinAt_tsum h
theorem lowerSemicontinuousOn_tsum {f : ι → α → ℝ≥0∞} (h : ∀ i, LowerSemicontinuousOn (f i) s) :
LowerSemicontinuousOn (fun x' => ∑' i, f i x') s := fun x hx =>
lowerSemicontinuousWithinAt_tsum fun i => h i x hx
theorem lowerSemicontinuous_tsum {f : ι → α → ℝ≥0∞} (h : ∀ i, LowerSemicontinuous (f i)) :
LowerSemicontinuous fun x' => ∑' i, f i x' := fun x => lowerSemicontinuousAt_tsum fun i => h i x
end
/-!
### Upper semicontinuous functions
-/
/-! #### Basic dot notation interface for upper semicontinuity -/
theorem UpperSemicontinuousWithinAt.mono (h : UpperSemicontinuousWithinAt f s x) (hst : t ⊆ s) :
UpperSemicontinuousWithinAt f t x := fun y hy =>
Filter.Eventually.filter_mono (nhdsWithin_mono _ hst) (h y hy)
theorem upperSemicontinuousWithinAt_univ_iff :
UpperSemicontinuousWithinAt f univ x ↔ UpperSemicontinuousAt f x := by
simp [UpperSemicontinuousWithinAt, UpperSemicontinuousAt, nhdsWithin_univ]
theorem UpperSemicontinuousAt.upperSemicontinuousWithinAt (s : Set α)
(h : UpperSemicontinuousAt f x) : UpperSemicontinuousWithinAt f s x := fun y hy =>
Filter.Eventually.filter_mono nhdsWithin_le_nhds (h y hy)
theorem UpperSemicontinuousOn.upperSemicontinuousWithinAt (h : UpperSemicontinuousOn f s)
(hx : x ∈ s) : UpperSemicontinuousWithinAt f s x :=
h x hx
theorem UpperSemicontinuousOn.mono (h : UpperSemicontinuousOn f s) (hst : t ⊆ s) :
UpperSemicontinuousOn f t := fun x hx => (h x (hst hx)).mono hst
| Mathlib/Topology/Semicontinuous.lean | 691 | 693 | theorem upperSemicontinuousOn_univ_iff : UpperSemicontinuousOn f univ ↔ UpperSemicontinuous f := by | simp [UpperSemicontinuousOn, UpperSemicontinuous, upperSemicontinuousWithinAt_univ_iff] |
/-
Copyright (c) 2022 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.NumberTheory.Cyclotomic.Discriminant
import Mathlib.RingTheory.Polynomial.Eisenstein.IsIntegral
import Mathlib.RingTheory.Ideal.Norm.AbsNorm
import Mathlib.RingTheory.Prime
/-!
# Ring of integers of `p ^ n`-th cyclotomic fields
We gather results about cyclotomic extensions of `ℚ`. In particular, we compute the ring of
integers of a `p ^ n`-th cyclotomic extension of `ℚ`.
## Main results
* `IsCyclotomicExtension.Rat.isIntegralClosure_adjoin_singleton_of_prime_pow`: if `K` is a
`p ^ k`-th cyclotomic extension of `ℚ`, then `(adjoin ℤ {ζ})` is the integral closure of
`ℤ` in `K`.
* `IsCyclotomicExtension.Rat.cyclotomicRing_isIntegralClosure_of_prime_pow`: the integral
closure of `ℤ` inside `CyclotomicField (p ^ k) ℚ` is `CyclotomicRing (p ^ k) ℤ ℚ`.
* `IsCyclotomicExtension.Rat.absdiscr_prime_pow` and related results: the absolute discriminant
of cyclotomic fields.
-/
universe u
open Algebra IsCyclotomicExtension Polynomial NumberField
open scoped Cyclotomic Nat
variable {p : ℕ+} {k : ℕ} {K : Type u} [Field K] {ζ : K} [hp : Fact (p : ℕ).Prime]
namespace IsCyclotomicExtension.Rat
variable [CharZero K]
/-- The discriminant of the power basis given by `ζ - 1`. -/
theorem discr_prime_pow_ne_two' [IsCyclotomicExtension {p ^ (k + 1)} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ (k + 1))) (hk : p ^ (k + 1) ≠ 2) :
discr ℚ (hζ.subOnePowerBasis ℚ).basis =
(-1) ^ ((p ^ (k + 1) : ℕ).totient / 2) * p ^ ((p : ℕ) ^ k * ((p - 1) * (k + 1) - 1)) := by
rw [← discr_prime_pow_ne_two hζ (cyclotomic.irreducible_rat (p ^ (k + 1)).pos) hk]
exact hζ.discr_zeta_eq_discr_zeta_sub_one.symm
theorem discr_odd_prime' [IsCyclotomicExtension {p} ℚ K] (hζ : IsPrimitiveRoot ζ p) (hodd : p ≠ 2) :
discr ℚ (hζ.subOnePowerBasis ℚ).basis = (-1) ^ (((p : ℕ) - 1) / 2) * p ^ ((p : ℕ) - 2) := by
rw [← discr_odd_prime hζ (cyclotomic.irreducible_rat hp.out.pos) hodd]
exact hζ.discr_zeta_eq_discr_zeta_sub_one.symm
/-- The discriminant of the power basis given by `ζ - 1`. Beware that in the cases `p ^ k = 1` and
`p ^ k = 2` the formula uses `1 / 2 = 0` and `0 - 1 = 0`. It is useful only to have a uniform
result. See also `IsCyclotomicExtension.Rat.discr_prime_pow_eq_unit_mul_pow'`. -/
theorem discr_prime_pow' [IsCyclotomicExtension {p ^ k} ℚ K] (hζ : IsPrimitiveRoot ζ ↑(p ^ k)) :
discr ℚ (hζ.subOnePowerBasis ℚ).basis =
(-1) ^ ((p ^ k : ℕ).totient / 2) * p ^ ((p : ℕ) ^ (k - 1) * ((p - 1) * k - 1)) := by
rw [← discr_prime_pow hζ (cyclotomic.irreducible_rat (p ^ k).pos)]
exact hζ.discr_zeta_eq_discr_zeta_sub_one.symm
/-- If `p` is a prime and `IsCyclotomicExtension {p ^ k} K L`, then there are `u : ℤˣ` and
`n : ℕ` such that the discriminant of the power basis given by `ζ - 1` is `u * p ^ n`. Often this is
enough and less cumbersome to use than `IsCyclotomicExtension.Rat.discr_prime_pow'`. -/
theorem discr_prime_pow_eq_unit_mul_pow' [IsCyclotomicExtension {p ^ k} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ k)) :
∃ (u : ℤˣ) (n : ℕ), discr ℚ (hζ.subOnePowerBasis ℚ).basis = u * p ^ n := by
rw [hζ.discr_zeta_eq_discr_zeta_sub_one.symm]
exact discr_prime_pow_eq_unit_mul_pow hζ (cyclotomic.irreducible_rat (p ^ k).pos)
/-- If `K` is a `p ^ k`-th cyclotomic extension of `ℚ`, then `(adjoin ℤ {ζ})` is the
integral closure of `ℤ` in `K`. -/
theorem isIntegralClosure_adjoin_singleton_of_prime_pow [hcycl : IsCyclotomicExtension {p ^ k} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ k)) : IsIntegralClosure (adjoin ℤ ({ζ} : Set K)) ℤ K := by
refine ⟨Subtype.val_injective, @fun x => ⟨fun h => ⟨⟨x, ?_⟩, rfl⟩, ?_⟩⟩
swap
· rintro ⟨y, rfl⟩
exact
IsIntegral.algebraMap
((le_integralClosure_iff_isIntegral.1
(adjoin_le_integralClosure (hζ.isIntegral (p ^ k).pos))).isIntegral _)
let B := hζ.subOnePowerBasis ℚ
have hint : IsIntegral ℤ B.gen := (hζ.isIntegral (p ^ k).pos).sub isIntegral_one
-- Porting note: the following `letI` was not needed because the locale `cyclotomic` set it
-- as instances.
letI := IsCyclotomicExtension.finiteDimensional {p ^ k} ℚ K
have H := discr_mul_isIntegral_mem_adjoin ℚ hint h
obtain ⟨u, n, hun⟩ := discr_prime_pow_eq_unit_mul_pow' hζ
rw [hun] at H
replace H := Subalgebra.smul_mem _ H u.inv
rw [← smul_assoc, ← smul_mul_assoc, Units.inv_eq_val_inv, zsmul_eq_mul, ← Int.cast_mul,
Units.inv_mul, Int.cast_one, one_mul, smul_def, map_pow] at H
cases k
· haveI : IsCyclotomicExtension {1} ℚ K := by simpa using hcycl
have : x ∈ (⊥ : Subalgebra ℚ K) := by
rw [singleton_one ℚ K]
exact mem_top
obtain ⟨y, rfl⟩ := mem_bot.1 this
replace h := (isIntegral_algebraMap_iff (algebraMap ℚ K).injective).1 h
obtain ⟨z, hz⟩ := IsIntegrallyClosed.isIntegral_iff.1 h
rw [← hz, ← IsScalarTower.algebraMap_apply]
exact Subalgebra.algebraMap_mem _ _
· have hmin : (minpoly ℤ B.gen).IsEisensteinAt (Submodule.span ℤ {((p : ℕ) : ℤ)}) := by
have h₁ := minpoly.isIntegrallyClosed_eq_field_fractions' ℚ hint
have h₂ := hζ.minpoly_sub_one_eq_cyclotomic_comp (cyclotomic.irreducible_rat (p ^ _).pos)
rw [IsPrimitiveRoot.subOnePowerBasis_gen] at h₁
rw [h₁, ← map_cyclotomic_int, show Int.castRingHom ℚ = algebraMap ℤ ℚ by rfl,
show X + 1 = map (algebraMap ℤ ℚ) (X + 1) by simp, ← map_comp] at h₂
rw [IsPrimitiveRoot.subOnePowerBasis_gen,
map_injective (algebraMap ℤ ℚ) (algebraMap ℤ ℚ).injective_int h₂]
exact cyclotomic_prime_pow_comp_X_add_one_isEisensteinAt p _
refine
adjoin_le ?_
(mem_adjoin_of_smul_prime_pow_smul_of_minpoly_isEisensteinAt (n := n)
(Nat.prime_iff_prime_int.1 hp.out) hint h (by simpa using H) hmin)
simp only [Set.singleton_subset_iff, SetLike.mem_coe]
exact Subalgebra.sub_mem _ (self_mem_adjoin_singleton ℤ _) (Subalgebra.one_mem _)
theorem isIntegralClosure_adjoin_singleton_of_prime [hcycl : IsCyclotomicExtension {p} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑p) : IsIntegralClosure (adjoin ℤ ({ζ} : Set K)) ℤ K := by
rw [← pow_one p] at hζ hcycl
exact isIntegralClosure_adjoin_singleton_of_prime_pow hζ
/-- The integral closure of `ℤ` inside `CyclotomicField (p ^ k) ℚ` is
`CyclotomicRing (p ^ k) ℤ ℚ`. -/
theorem cyclotomicRing_isIntegralClosure_of_prime_pow :
IsIntegralClosure (CyclotomicRing (p ^ k) ℤ ℚ) ℤ (CyclotomicField (p ^ k) ℚ) := by
have hζ := zeta_spec (p ^ k) ℚ (CyclotomicField (p ^ k) ℚ)
refine ⟨IsFractionRing.injective _ _, @fun x => ⟨fun h => ⟨⟨x, ?_⟩, rfl⟩, ?_⟩⟩
· obtain ⟨y, rfl⟩ := (isIntegralClosure_adjoin_singleton_of_prime_pow hζ).isIntegral_iff.1 h
refine adjoin_mono ?_ y.2
simp only [PNat.pow_coe, Set.singleton_subset_iff, Set.mem_setOf_eq]
exact hζ.pow_eq_one
· rintro ⟨y, rfl⟩
exact IsIntegral.algebraMap ((IsCyclotomicExtension.integral {p ^ k} ℤ _).isIntegral _)
theorem cyclotomicRing_isIntegralClosure_of_prime :
IsIntegralClosure (CyclotomicRing p ℤ ℚ) ℤ (CyclotomicField p ℚ) := by
rw [← pow_one p]
exact cyclotomicRing_isIntegralClosure_of_prime_pow
end IsCyclotomicExtension.Rat
section PowerBasis
open IsCyclotomicExtension.Rat
namespace IsPrimitiveRoot
section CharZero
variable [CharZero K]
/-- The algebra isomorphism `adjoin ℤ {ζ} ≃ₐ[ℤ] (𝓞 K)`, where `ζ` is a primitive `p ^ k`-th root of
unity and `K` is a `p ^ k`-th cyclotomic extension of `ℚ`. -/
@[simps!]
noncomputable def _root_.IsPrimitiveRoot.adjoinEquivRingOfIntegers
[IsCyclotomicExtension {p ^ k} ℚ K] (hζ : IsPrimitiveRoot ζ ↑(p ^ k)) :
adjoin ℤ ({ζ} : Set K) ≃ₐ[ℤ] 𝓞 K :=
let _ := isIntegralClosure_adjoin_singleton_of_prime_pow hζ
IsIntegralClosure.equiv ℤ (adjoin ℤ ({ζ} : Set K)) K (𝓞 K)
/-- The ring of integers of a `p ^ k`-th cyclotomic extension of `ℚ` is a cyclotomic extension. -/
instance IsCyclotomicExtension.ringOfIntegers [IsCyclotomicExtension {p ^ k} ℚ K] :
IsCyclotomicExtension {p ^ k} ℤ (𝓞 K) :=
let _ := (zeta_spec (p ^ k) ℚ K).adjoin_isCyclotomicExtension ℤ
IsCyclotomicExtension.equiv _ ℤ _ (zeta_spec (p ^ k) ℚ K).adjoinEquivRingOfIntegers
/-- The integral `PowerBasis` of `𝓞 K` given by a primitive root of unity, where `K` is a `p ^ k`
cyclotomic extension of `ℚ`. -/
noncomputable def integralPowerBasis [IsCyclotomicExtension {p ^ k} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ k)) : PowerBasis ℤ (𝓞 K) :=
(Algebra.adjoin.powerBasis' (hζ.isIntegral (p ^ k).pos)).map hζ.adjoinEquivRingOfIntegers
/-- Abbreviation to see a primitive root of unity as a member of the ring of integers. -/
abbrev toInteger {k : ℕ+} (hζ : IsPrimitiveRoot ζ k) : 𝓞 K := ⟨ζ, hζ.isIntegral k.pos⟩
end CharZero
lemma coe_toInteger {k : ℕ+} (hζ : IsPrimitiveRoot ζ k) : hζ.toInteger.1 = ζ := rfl
/-- `𝓞 K ⧸ Ideal.span {ζ - 1}` is finite. -/
lemma finite_quotient_toInteger_sub_one [NumberField K] {k : ℕ+} (hk : 1 < k)
(hζ : IsPrimitiveRoot ζ k) : Finite (𝓞 K ⧸ Ideal.span {hζ.toInteger - 1}) := by
refine Ideal.finiteQuotientOfFreeOfNeBot _ (fun h ↦ ?_)
simp only [Ideal.span_singleton_eq_bot, sub_eq_zero, ← Subtype.coe_inj] at h
exact hζ.ne_one hk (RingOfIntegers.ext_iff.1 h)
/-- We have that `𝓞 K ⧸ Ideal.span {ζ - 1}` has cardinality equal to the norm of `ζ - 1`.
See the results below to compute this norm in various cases. -/
lemma card_quotient_toInteger_sub_one [NumberField K] {k : ℕ+} (hζ : IsPrimitiveRoot ζ k) :
Nat.card (𝓞 K ⧸ Ideal.span {hζ.toInteger - 1}) =
(Algebra.norm ℤ (hζ.toInteger - 1)).natAbs := by
rw [← Submodule.cardQuot_apply, ← Ideal.absNorm_apply, Ideal.absNorm_span_singleton]
lemma toInteger_isPrimitiveRoot {k : ℕ+} (hζ : IsPrimitiveRoot ζ k) :
IsPrimitiveRoot hζ.toInteger k :=
IsPrimitiveRoot.of_map_of_injective (by exact hζ) RingOfIntegers.coe_injective
variable [CharZero K]
@[simp]
theorem integralPowerBasis_gen [hcycl : IsCyclotomicExtension {p ^ k} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ k)) :
hζ.integralPowerBasis.gen = hζ.toInteger :=
Subtype.ext <| show algebraMap _ K hζ.integralPowerBasis.gen = _ by
rw [integralPowerBasis, PowerBasis.map_gen, adjoin.powerBasis'_gen]
simp only [adjoinEquivRingOfIntegers_apply, IsIntegralClosure.algebraMap_lift]
rfl
#adaptation_note /-- https://github.com/leanprover/lean4/pull/5338
We name `hcycl` so it can be used as a named argument,
but since https://github.com/leanprover/lean4/pull/5338, this is considered unused,
so we need to disable the linter. -/
set_option linter.unusedVariables false in
@[simp]
theorem integralPowerBasis_dim [hcycl : IsCyclotomicExtension {p ^ k} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ k)) : hζ.integralPowerBasis.dim = φ (p ^ k) := by
simp [integralPowerBasis, ← cyclotomic_eq_minpoly hζ, natDegree_cyclotomic]
/-- The algebra isomorphism `adjoin ℤ {ζ} ≃ₐ[ℤ] (𝓞 K)`, where `ζ` is a primitive `p`-th root of
unity and `K` is a `p`-th cyclotomic extension of `ℚ`. -/
@[simps!]
noncomputable def _root_.IsPrimitiveRoot.adjoinEquivRingOfIntegers'
[hcycl : IsCyclotomicExtension {p} ℚ K] (hζ : IsPrimitiveRoot ζ p) :
adjoin ℤ ({ζ} : Set K) ≃ₐ[ℤ] 𝓞 K :=
have : IsCyclotomicExtension {p ^ 1} ℚ K := by convert hcycl; rw [pow_one]
adjoinEquivRingOfIntegers (p := p) (k := 1) (ζ := ζ) (by rwa [pow_one])
/-- The ring of integers of a `p`-th cyclotomic extension of `ℚ` is a cyclotomic extension. -/
instance _root_.IsCyclotomicExtension.ring_of_integers' [IsCyclotomicExtension {p} ℚ K] :
IsCyclotomicExtension {p} ℤ (𝓞 K) :=
let _ := (zeta_spec p ℚ K).adjoin_isCyclotomicExtension ℤ
IsCyclotomicExtension.equiv _ ℤ _ (zeta_spec p ℚ K).adjoinEquivRingOfIntegers'
/-- The integral `PowerBasis` of `𝓞 K` given by a primitive root of unity, where `K` is a `p`-th
cyclotomic extension of `ℚ`. -/
noncomputable def integralPowerBasis' [hcycl : IsCyclotomicExtension {p} ℚ K]
(hζ : IsPrimitiveRoot ζ p) : PowerBasis ℤ (𝓞 K) :=
have : IsCyclotomicExtension {p ^ 1} ℚ K := by convert hcycl; rw [pow_one]
integralPowerBasis (p := p) (k := 1) (ζ := ζ) (by rwa [pow_one])
@[simp]
theorem integralPowerBasis'_gen [hcycl : IsCyclotomicExtension {p} ℚ K] (hζ : IsPrimitiveRoot ζ p) :
hζ.integralPowerBasis'.gen = hζ.toInteger :=
integralPowerBasis_gen (hcycl := by rwa [pow_one]) (by rwa [pow_one])
@[simp]
theorem power_basis_int'_dim [hcycl : IsCyclotomicExtension {p} ℚ K] (hζ : IsPrimitiveRoot ζ p) :
hζ.integralPowerBasis'.dim = φ p := by
rw [integralPowerBasis', integralPowerBasis_dim (hcycl := by rwa [pow_one]) (by rwa [pow_one]),
pow_one]
/-- The integral `PowerBasis` of `𝓞 K` given by `ζ - 1`, where `K` is a `p ^ k` cyclotomic
extension of `ℚ`. -/
noncomputable def subOneIntegralPowerBasis [IsCyclotomicExtension {p ^ k} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ k)) : PowerBasis ℤ (𝓞 K) :=
PowerBasis.ofGenMemAdjoin' hζ.integralPowerBasis (RingOfIntegers.isIntegral _)
(by
simp only [integralPowerBasis_gen, toInteger]
convert Subalgebra.add_mem _ (self_mem_adjoin_singleton ℤ (⟨ζ - 1, _⟩ : 𝓞 K))
(Subalgebra.one_mem _)
· simp
· exact Subalgebra.sub_mem _ (hζ.isIntegral (by simp)) (Subalgebra.one_mem _))
@[simp]
theorem subOneIntegralPowerBasis_gen [IsCyclotomicExtension {p ^ k} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ k)) :
hζ.subOneIntegralPowerBasis.gen =
⟨ζ - 1, Subalgebra.sub_mem _ (hζ.isIntegral (p ^ k).pos) (Subalgebra.one_mem _)⟩ := by
simp [subOneIntegralPowerBasis]
/-- The integral `PowerBasis` of `𝓞 K` given by `ζ - 1`, where `K` is a `p`-th cyclotomic
extension of `ℚ`. -/
noncomputable def subOneIntegralPowerBasis' [IsCyclotomicExtension {p} ℚ K]
(hζ : IsPrimitiveRoot ζ p) : PowerBasis ℤ (𝓞 K) :=
have : IsCyclotomicExtension {p ^ 1} ℚ K := by rwa [pow_one]
subOneIntegralPowerBasis (p := p) (k := 1) (ζ := ζ) (by rwa [pow_one])
@[simp, nolint unusedHavesSuffices]
theorem subOneIntegralPowerBasis'_gen [IsCyclotomicExtension {p} ℚ K]
(hζ : IsPrimitiveRoot ζ p) :
hζ.subOneIntegralPowerBasis'.gen = hζ.toInteger - 1 :=
-- The `unusedHavesSuffices` linter incorrectly thinks this `have` is unnecessary.
have : IsCyclotomicExtension {p ^ 1} ℚ K := by rwa [pow_one]
subOneIntegralPowerBasis_gen (by rwa [pow_one])
/-- `ζ - 1` is prime if `p ≠ 2` and `ζ` is a primitive `p ^ (k + 1)`-th root of unity.
See `zeta_sub_one_prime` for a general statement. -/
theorem zeta_sub_one_prime_of_ne_two [IsCyclotomicExtension {p ^ (k + 1)} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ (k + 1))) (hodd : p ≠ 2) :
Prime (hζ.toInteger - 1) := by
letI := IsCyclotomicExtension.numberField {p ^ (k + 1)} ℚ K
refine Ideal.prime_of_irreducible_absNorm_span (fun h ↦ ?_) ?_
· apply hζ.pow_ne_one_of_pos_of_lt zero_lt_one (one_lt_pow₀ hp.out.one_lt (by simp))
rw [sub_eq_zero] at h
simpa using congrArg (algebraMap _ K) h
rw [Nat.irreducible_iff_prime, Ideal.absNorm_span_singleton, ← Nat.prime_iff,
← Int.prime_iff_natAbs_prime]
convert Nat.prime_iff_prime_int.1 hp.out
apply RingHom.injective_int (algebraMap ℤ ℚ)
rw [← Algebra.norm_localization (Sₘ := K) ℤ (nonZeroDivisors ℤ)]
simp only [PNat.pow_coe, id.map_eq_id, RingHomCompTriple.comp_eq, RingHom.coe_coe,
Subalgebra.coe_val, algebraMap_int_eq, map_natCast]
exact hζ.norm_sub_one_of_prime_ne_two (Polynomial.cyclotomic.irreducible_rat (PNat.pos _)) hodd
/-- `ζ - 1` is prime if `ζ` is a primitive `2 ^ (k + 1)`-th root of unity.
See `zeta_sub_one_prime` for a general statement. -/
theorem zeta_sub_one_prime_of_two_pow [IsCyclotomicExtension {(2 : ℕ+) ^ (k + 1)} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑((2 : ℕ+) ^ (k + 1))) :
Prime (hζ.toInteger - 1) := by
letI := IsCyclotomicExtension.numberField {(2 : ℕ+) ^ (k + 1)} ℚ K
refine Ideal.prime_of_irreducible_absNorm_span (fun h ↦ ?_) ?_
· apply hζ.pow_ne_one_of_pos_of_lt zero_lt_one (one_lt_pow₀ (by decide) (by simp))
rw [sub_eq_zero] at h
simpa using congrArg (algebraMap _ K) h
rw [Nat.irreducible_iff_prime, Ideal.absNorm_span_singleton, ← Nat.prime_iff,
← Int.prime_iff_natAbs_prime]
cases k
· convert Prime.neg Int.prime_two
apply RingHom.injective_int (algebraMap ℤ ℚ)
rw [← Algebra.norm_localization (Sₘ := K) ℤ (nonZeroDivisors ℤ)]
simp only [PNat.pow_coe, id.map_eq_id, RingHomCompTriple.comp_eq, RingHom.coe_coe,
Subalgebra.coe_val, algebraMap_int_eq, map_neg, map_ofNat]
simpa only [zero_add, pow_one, AddSubgroupClass.coe_sub, OneMemClass.coe_one,
pow_zero]
using hζ.norm_pow_sub_one_two (cyclotomic.irreducible_rat
(by simp only [zero_add, pow_one, Nat.ofNat_pos]))
convert Int.prime_two
apply RingHom.injective_int (algebraMap ℤ ℚ)
rw [← Algebra.norm_localization (Sₘ := K) ℤ (nonZeroDivisors ℤ)]
simp only [PNat.pow_coe, id.map_eq_id, RingHomCompTriple.comp_eq, RingHom.coe_coe,
Subalgebra.coe_val, algebraMap_int_eq, map_natCast]
exact hζ.norm_sub_one_two Nat.AtLeastTwo.prop (cyclotomic.irreducible_rat (by simp))
/-- `ζ - 1` is prime if `ζ` is a primitive `p ^ (k + 1)`-th root of unity. -/
theorem zeta_sub_one_prime [IsCyclotomicExtension {p ^ (k + 1)} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ (k + 1))) : Prime (hζ.toInteger - 1) := by
by_cases htwo : p = 2
· subst htwo
apply hζ.zeta_sub_one_prime_of_two_pow
· apply hζ.zeta_sub_one_prime_of_ne_two htwo
/-- `ζ - 1` is prime if `ζ` is a primitive `p`-th root of unity. -/
theorem zeta_sub_one_prime' [h : IsCyclotomicExtension {p} ℚ K] (hζ : IsPrimitiveRoot ζ p) :
Prime ((hζ.toInteger - 1)) := by
convert zeta_sub_one_prime (k := 0) (by simpa only [zero_add, pow_one])
simpa only [zero_add, pow_one]
| Mathlib/NumberTheory/Cyclotomic/Rat.lean | 350 | 355 | theorem subOneIntegralPowerBasis_gen_prime [IsCyclotomicExtension {p ^ (k + 1)} ℚ K]
(hζ : IsPrimitiveRoot ζ ↑(p ^ (k + 1))) :
Prime hζ.subOneIntegralPowerBasis.gen := by | simpa only [subOneIntegralPowerBasis_gen] using hζ.zeta_sub_one_prime
theorem subOneIntegralPowerBasis'_gen_prime [IsCyclotomicExtension {p} ℚ K] |
/-
Copyright (c) 2023 Xavier Roblot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Xavier Roblot
-/
import Mathlib.Data.Complex.FiniteDimensional
import Mathlib.MeasureTheory.Constructions.HaarToSphere
import Mathlib.MeasureTheory.Integral.Gamma
import Mathlib.MeasureTheory.Integral.Pi
import Mathlib.Analysis.SpecialFunctions.Gaussian.GaussianIntegral
/-!
# Volume of balls
Let `E` be a finite dimensional normed `ℝ`-vector space equipped with a Haar measure `μ`. We
prove that
`μ (Metric.ball 0 1) = (∫ (x : E), Real.exp (- ‖x‖ ^ p) ∂μ) / Real.Gamma (finrank ℝ E / p + 1)`
for any real number `p` with `0 < p`, see `MeasureTheorymeasure_unitBall_eq_integral_div_gamma`. We
also prove the corresponding result to compute `μ {x : E | g x < 1}` where `g : E → ℝ` is a function
defining a norm on `E`, see `MeasureTheory.measure_lt_one_eq_integral_div_gamma`.
Using these formulas, we compute the volume of the unit balls in several cases.
* `MeasureTheory.volume_sum_rpow_lt` / `MeasureTheory.volume_sum_rpow_le`: volume of the open and
closed balls for the norm `Lp` over a real finite dimensional vector space with `1 ≤ p`. These
are computed as `volume {x : ι → ℝ | (∑ i, |x i| ^ p) ^ (1 / p) < r}` and
`volume {x : ι → ℝ | (∑ i, |x i| ^ p) ^ (1 / p) ≤ r}` since the spaces `PiLp` do not have a
`MeasureSpace` instance.
* `Complex.volume_sum_rpow_lt_one` / `Complex.volume_sum_rpow_lt`: same as above but for complex
finite dimensional vector space.
* `EuclideanSpace.volume_ball` / `EuclideanSpace.volume_closedBall` : volume of open and closed
balls in a finite dimensional Euclidean space.
* `InnerProductSpace.volume_ball` / `InnerProductSpace.volume_closedBall`: volume of open and closed
balls in a finite dimensional real inner product space.
* `Complex.volume_ball` / `Complex.volume_closedBall`: volume of open and closed balls in `ℂ`.
-/
section general_case
open MeasureTheory MeasureTheory.Measure Module ENNReal
theorem MeasureTheory.measure_unitBall_eq_integral_div_gamma {E : Type*} {p : ℝ}
[NormedAddCommGroup E] [NormedSpace ℝ E] [FiniteDimensional ℝ E] [MeasurableSpace E]
[BorelSpace E] (μ : Measure E) [IsAddHaarMeasure μ] (hp : 0 < p) :
μ (Metric.ball 0 1) =
.ofReal ((∫ (x : E), Real.exp (- ‖x‖ ^ p) ∂μ) / Real.Gamma (finrank ℝ E / p + 1)) := by
obtain hE | hE := subsingleton_or_nontrivial E
· rw [(Metric.nonempty_ball.mpr zero_lt_one).eq_zero, ← setIntegral_univ,
Set.univ_nonempty.eq_zero, integral_singleton, finrank_zero_of_subsingleton, Nat.cast_zero,
zero_div, zero_add, Real.Gamma_one, div_one, norm_zero, Real.zero_rpow hp.ne', neg_zero,
Real.exp_zero, smul_eq_mul, mul_one, measureReal_def, ofReal_toReal (measure_ne_top μ {0})]
· have : (0 : ℝ) < finrank ℝ E := Nat.cast_pos.mpr finrank_pos
have : ((∫ y in Set.Ioi (0 : ℝ), y ^ (finrank ℝ E - 1) • Real.exp (-y ^ p)) /
Real.Gamma ((finrank ℝ E) / p + 1)) * (finrank ℝ E) = 1 := by
simp_rw [← Real.rpow_natCast _ (finrank ℝ E - 1), smul_eq_mul, Nat.cast_sub finrank_pos,
Nat.cast_one]
rw [integral_rpow_mul_exp_neg_rpow hp (by linarith), sub_add_cancel,
Real.Gamma_add_one (ne_of_gt (by positivity))]
field_simp; ring
rw [integral_fun_norm_addHaar μ (fun x => Real.exp (- x ^ p)), nsmul_eq_mul, smul_eq_mul,
mul_div_assoc, mul_div_assoc, mul_comm, mul_assoc, this, mul_one, ofReal_measureReal _]
exact ne_of_lt measure_ball_lt_top
variable {E : Type*} [AddCommGroup E] [Module ℝ E] [FiniteDimensional ℝ E] [mE : MeasurableSpace E]
[tE : TopologicalSpace E] [IsTopologicalAddGroup E] [BorelSpace E] [T2Space E]
[ContinuousSMul ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {g : E → ℝ} (h1 : g 0 = 0)
(h2 : ∀ x, g (-x) = g x) (h3 : ∀ x y, g (x + y) ≤ g x + g y) (h4 : ∀ {x}, g x = 0 → x = 0)
(h5 : ∀ r x, g (r • x) ≤ |r| * (g x))
include h1 h2 h3 h4 h5
theorem MeasureTheory.measure_lt_one_eq_integral_div_gamma {p : ℝ} (hp : 0 < p) :
μ {x : E | g x < 1} =
.ofReal ((∫ (x : E), Real.exp (- (g x) ^ p) ∂μ) / Real.Gamma (finrank ℝ E / p + 1)) := by
-- We copy `E` to a new type `F` on which we will put the norm defined by `g`
letI F : Type _ := E
letI : NormedAddCommGroup F :=
{ norm := g
dist := fun x y => g (x - y)
dist_self := by simp only [_root_.sub_self, h1, forall_const]
dist_comm := fun _ _ => by rw [← h2, neg_sub]
dist_triangle := fun x y z => by convert h3 (x - y) (y - z) using 1; simp [F]
edist := fun x y => .ofReal (g (x - y))
edist_dist := fun _ _ => rfl
eq_of_dist_eq_zero := by convert fun _ _ h => eq_of_sub_eq_zero (h4 h) }
letI : NormedSpace ℝ F :=
{ norm_smul_le := fun _ _ ↦ h5 _ _ }
-- We put the new topology on F
letI : TopologicalSpace F := UniformSpace.toTopologicalSpace
letI : MeasurableSpace F := borel F
have : BorelSpace F := { measurable_eq := rfl }
-- The map between `E` and `F` as a continuous linear equivalence
let φ := @LinearEquiv.toContinuousLinearEquiv ℝ _ E _ _ tE _ _ F _ _ _ _ _ _ _ _ _
(LinearEquiv.refl ℝ E : E ≃ₗ[ℝ] F)
-- The measure `ν` is the measure on `F` defined by `μ`
-- Since we have two different topologies, it is necessary to specify the topology of E
let ν : Measure F := @Measure.map E F mE _ φ μ
have : IsAddHaarMeasure ν :=
@ContinuousLinearEquiv.isAddHaarMeasure_map E F ℝ ℝ _ _ _ _ _ _ tE _ _ _ _ _ _ _ mE _ _ _ φ μ _
convert (measure_unitBall_eq_integral_div_gamma ν hp) using 1
· rw [@Measure.map_apply E F mE _ μ φ _ _ measurableSet_ball]
· congr!
simp_rw [Metric.ball, dist_zero_right]
rfl
· refine @Continuous.measurable E F tE mE _ _ _ _ φ ?_
exact @ContinuousLinearEquiv.continuous ℝ ℝ _ _ _ _ _ _ E tE _ F _ _ _ _ φ
· -- The map between `E` and `F` as a measurable equivalence
let ψ := @Homeomorph.toMeasurableEquiv E F tE mE _ _ _ _
(@ContinuousLinearEquiv.toHomeomorph ℝ ℝ _ _ _ _ _ _ E tE _ F _ _ _ _ φ)
-- The map `ψ` is measure preserving by construction
have : @MeasurePreserving E F mE _ ψ μ ν :=
@Measurable.measurePreserving E F mE _ ψ (@MeasurableEquiv.measurable E F mE _ ψ) _
rw [← this.integral_comp']
rfl
theorem MeasureTheory.measure_le_eq_lt [Nontrivial E] (r : ℝ) :
μ {x : E | g x ≤ r} = μ {x : E | g x < r} := by
-- We copy `E` to a new type `F` on which we will put the norm defined by `g`
letI F : Type _ := E
letI : NormedAddCommGroup F :=
{ norm := g
dist := fun x y => g (x - y)
dist_self := by simp only [_root_.sub_self, h1, forall_const]
dist_comm := fun _ _ => by rw [← h2, neg_sub]
dist_triangle := fun x y z => by convert h3 (x - y) (y - z) using 1; simp [F]
edist := fun x y => .ofReal (g (x - y))
edist_dist := fun _ _ => rfl
eq_of_dist_eq_zero := by convert fun _ _ h => eq_of_sub_eq_zero (h4 h) }
letI : NormedSpace ℝ F :=
{ norm_smul_le := fun _ _ ↦ h5 _ _ }
-- We put the new topology on F
letI : TopologicalSpace F := UniformSpace.toTopologicalSpace
letI : MeasurableSpace F := borel F
have : BorelSpace F := { measurable_eq := rfl }
-- The map between `E` and `F` as a continuous linear equivalence
let φ := @LinearEquiv.toContinuousLinearEquiv ℝ _ E _ _ tE _ _ F _ _ _ _ _ _ _ _ _
(LinearEquiv.refl ℝ E : E ≃ₗ[ℝ] F)
-- The measure `ν` is the measure on `F` defined by `μ`
-- Since we have two different topologies, it is necessary to specify the topology of E
let ν : Measure F := @Measure.map E F mE _ φ μ
have : IsAddHaarMeasure ν :=
@ContinuousLinearEquiv.isAddHaarMeasure_map E F ℝ ℝ _ _ _ _ _ _ tE _ _ _ _ _ _ _ mE _ _ _ φ μ _
convert addHaar_closedBall_eq_addHaar_ball ν 0 r using 1
· rw [@Measure.map_apply E F mE _ μ φ _ _ measurableSet_closedBall]
· congr!
simp_rw [Metric.closedBall, dist_zero_right]
rfl
· refine @Continuous.measurable E F tE mE _ _ _ _ φ ?_
exact @ContinuousLinearEquiv.continuous ℝ ℝ _ _ _ _ _ _ E tE _ F _ _ _ _ φ
· rw [@Measure.map_apply E F mE _ μ φ _ _ measurableSet_ball]
· congr!
simp_rw [Metric.ball, dist_zero_right]
rfl
· refine @Continuous.measurable E F tE mE _ _ _ _ φ ?_
exact @ContinuousLinearEquiv.continuous ℝ ℝ _ _ _ _ _ _ E tE _ F _ _ _ _ φ
end general_case
section LpSpace
open Real Fintype ENNReal Module MeasureTheory MeasureTheory.Measure
variable (ι : Type*) [Fintype ι] {p : ℝ}
theorem MeasureTheory.volume_sum_rpow_lt_one (hp : 1 ≤ p) :
volume {x : ι → ℝ | ∑ i, |x i| ^ p < 1} =
.ofReal ((2 * Gamma (1 / p + 1)) ^ card ι / Gamma (card ι / p + 1)) := by
have h₁ : 0 < p := by linarith
have h₂ : ∀ x : ι → ℝ, 0 ≤ ∑ i, |x i| ^ p := by
refine fun _ => Finset.sum_nonneg' ?_
exact fun i => (fun _ => rpow_nonneg (abs_nonneg _) _) _
-- We collect facts about `Lp` norms that will be used in `measure_lt_one_eq_integral_div_gamma`
have eq_norm := fun x : ι → ℝ => (PiLp.norm_eq_sum (p := .ofReal p) (f := x)
((toReal_ofReal (le_of_lt h₁)).symm ▸ h₁))
simp_rw [toReal_ofReal (le_of_lt h₁), Real.norm_eq_abs] at eq_norm
have : Fact (1 ≤ ENNReal.ofReal p) := fact_iff.mpr (ofReal_one ▸ (ofReal_le_ofReal hp))
have nm_zero := norm_zero (E := PiLp (.ofReal p) (fun _ : ι => ℝ))
have eq_zero := fun x : ι → ℝ => norm_eq_zero (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) (a := x)
have nm_neg := fun x : ι → ℝ => norm_neg (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) x
have nm_add := fun x y : ι → ℝ => norm_add_le (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) x y
simp_rw [eq_norm] at eq_zero nm_zero nm_neg nm_add
have nm_smul := fun (r : ℝ) (x : ι → ℝ) =>
norm_smul_le (β := PiLp (.ofReal p) (fun _ : ι => ℝ)) r x
simp_rw [eq_norm, norm_eq_abs] at nm_smul
-- We use `measure_lt_one_eq_integral_div_gamma` with `g` equals to the norm `L_p`
convert (measure_lt_one_eq_integral_div_gamma (volume : Measure (ι → ℝ))
(g := fun x => (∑ i, |x i| ^ p) ^ (1 / p)) nm_zero nm_neg nm_add (eq_zero _).mp
(fun r x => nm_smul r x) (by linarith : 0 < p)) using 4
· rw [rpow_lt_one_iff' _ (one_div_pos.mpr h₁)]
exact Finset.sum_nonneg' (fun _ => rpow_nonneg (abs_nonneg _) _)
· simp_rw [← rpow_mul (h₂ _), div_mul_cancel₀ _ (ne_of_gt h₁), Real.rpow_one,
← Finset.sum_neg_distrib, exp_sum]
rw [integral_fintype_prod_eq_pow ι fun x : ℝ => exp (- |x| ^ p), integral_comp_abs
(f := fun x => exp (- x ^ p)), integral_exp_neg_rpow h₁]
· rw [finrank_fintype_fun_eq_card]
theorem MeasureTheory.volume_sum_rpow_lt [Nonempty ι] {p : ℝ} (hp : 1 ≤ p) (r : ℝ) :
volume {x : ι → ℝ | (∑ i, |x i| ^ p) ^ (1 / p) < r} = (.ofReal r) ^ card ι *
.ofReal ((2 * Gamma (1 / p + 1)) ^ card ι / Gamma (card ι / p + 1)) := by
have h₁ (x : ι → ℝ) : 0 ≤ ∑ i, |x i| ^ p := by positivity
have h₂ : ∀ x : ι → ℝ, 0 ≤ (∑ i, |x i| ^ p) ^ (1 / p) := fun x => rpow_nonneg (h₁ x) _
obtain hr | hr := le_or_lt r 0
· have : {x : ι → ℝ | (∑ i, |x i| ^ p) ^ (1 / p) < r} = ∅ := by
ext x
refine ⟨fun hx => ?_, fun hx => hx.elim⟩
exact not_le.mpr (lt_of_lt_of_le (Set.mem_setOf.mp hx) hr) (h₂ x)
rw [this, measure_empty, ← zero_eq_ofReal.mpr hr, zero_pow Fin.pos'.ne', zero_mul]
· rw [← volume_sum_rpow_lt_one _ hp, ← ofReal_pow (le_of_lt hr), ← finrank_pi ℝ]
convert addHaar_smul_of_nonneg volume (le_of_lt hr) {x : ι → ℝ | ∑ i, |x i| ^ p < 1} using 2
simp_rw [← Set.preimage_smul_inv₀ (ne_of_gt hr), Set.preimage_setOf_eq, Pi.smul_apply,
smul_eq_mul, abs_mul, mul_rpow (abs_nonneg _) (abs_nonneg _), abs_inv,
inv_rpow (abs_nonneg _), ← Finset.mul_sum, abs_eq_self.mpr (le_of_lt hr),
inv_mul_lt_iff₀ (rpow_pos_of_pos hr _), mul_one, ← rpow_lt_rpow_iff
(rpow_nonneg (h₁ _) _) (le_of_lt hr) (by linarith : 0 < p), ← rpow_mul
(h₁ _), div_mul_cancel₀ _ (ne_of_gt (by linarith) : p ≠ 0), Real.rpow_one]
theorem MeasureTheory.volume_sum_rpow_le [Nonempty ι] {p : ℝ} (hp : 1 ≤ p) (r : ℝ) :
volume {x : ι → ℝ | (∑ i, |x i| ^ p) ^ (1 / p) ≤ r} = (.ofReal r) ^ card ι *
.ofReal ((2 * Gamma (1 / p + 1)) ^ card ι / Gamma (card ι / p + 1)) := by
have h₁ : 0 < p := by linarith
-- We collect facts about `Lp` norms that will be used in `measure_le_one_eq_lt_one`
have eq_norm := fun x : ι → ℝ => (PiLp.norm_eq_sum (p := .ofReal p) (f := x)
((toReal_ofReal (le_of_lt h₁)).symm ▸ h₁))
simp_rw [toReal_ofReal (le_of_lt h₁), Real.norm_eq_abs] at eq_norm
have : Fact (1 ≤ ENNReal.ofReal p) := fact_iff.mpr (ofReal_one ▸ (ofReal_le_ofReal hp))
have nm_zero := norm_zero (E := PiLp (.ofReal p) (fun _ : ι => ℝ))
have eq_zero := fun x : ι → ℝ => norm_eq_zero (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) (a := x)
have nm_neg := fun x : ι → ℝ => norm_neg (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) x
have nm_add := fun x y : ι → ℝ => norm_add_le (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) x y
simp_rw [eq_norm] at eq_zero nm_zero nm_neg nm_add
have nm_smul := fun (r : ℝ) (x : ι → ℝ) =>
norm_smul_le (β := PiLp (.ofReal p) (fun _ : ι => ℝ)) r x
simp_rw [eq_norm, norm_eq_abs] at nm_smul
rw [measure_le_eq_lt _ nm_zero (fun x ↦ nm_neg x) (fun x y ↦ nm_add x y) (eq_zero _).mp
(fun r x => nm_smul r x), volume_sum_rpow_lt _ hp]
| Mathlib/MeasureTheory/Measure/Lebesgue/VolumeOfBalls.lean | 240 | 271 | theorem Complex.volume_sum_rpow_lt_one {p : ℝ} (hp : 1 ≤ p) :
volume {x : ι → ℂ | ∑ i, ‖x i‖ ^ p < 1} =
.ofReal ((π * Real.Gamma (2 / p + 1)) ^ card ι / Real.Gamma (2 * card ι / p + 1)) := by | have h₁ : 0 < p := by linarith
have h₂ : ∀ x : ι → ℂ, 0 ≤ ∑ i, ‖x i‖ ^ p := by
refine fun _ => Finset.sum_nonneg' ?_
exact fun i => (fun _ => rpow_nonneg (norm_nonneg _) _) _
-- We collect facts about `Lp` norms that will be used in `measure_lt_one_eq_integral_div_gamma`
have eq_norm := fun x : ι → ℂ => (PiLp.norm_eq_sum (p := .ofReal p) (f := x)
((toReal_ofReal (le_of_lt h₁)).symm ▸ h₁))
simp_rw [toReal_ofReal (le_of_lt h₁)] at eq_norm
have : Fact (1 ≤ ENNReal.ofReal p) := fact_iff.mpr (ENNReal.ofReal_one ▸ (ofReal_le_ofReal hp))
have nm_zero := norm_zero (E := PiLp (.ofReal p) (fun _ : ι => ℂ))
have eq_zero := fun x : ι → ℂ => norm_eq_zero (E := PiLp (.ofReal p) (fun _ : ι => ℂ)) (a := x)
have nm_neg := fun x : ι → ℂ => norm_neg (E := PiLp (.ofReal p) (fun _ : ι => ℂ)) x
have nm_add := fun x y : ι → ℂ => norm_add_le (E := PiLp (.ofReal p) (fun _ : ι => ℂ)) x y
simp_rw [eq_norm] at eq_zero nm_zero nm_neg nm_add
have nm_smul := fun (r : ℝ) (x : ι → ℂ) =>
norm_smul_le (β := PiLp (.ofReal p) (fun _ : ι => ℂ)) r x
simp_rw [eq_norm] at nm_smul
-- We use `measure_lt_one_eq_integral_div_gamma` with `g` equals to the norm `L_p`
convert measure_lt_one_eq_integral_div_gamma (volume : Measure (ι → ℂ))
(g := fun x => (∑ i, ‖x i‖ ^ p) ^ (1 / p)) nm_zero nm_neg nm_add (eq_zero _).mp
(fun r x => nm_smul r x) (by linarith : 0 < p) using 4
· rw [rpow_lt_one_iff' _ (one_div_pos.mpr h₁)]
exact Finset.sum_nonneg' (fun _ => rpow_nonneg (norm_nonneg _) _)
· simp_rw [← rpow_mul (h₂ _), div_mul_cancel₀ _ (ne_of_gt h₁), Real.rpow_one,
← Finset.sum_neg_distrib, Real.exp_sum]
rw [integral_fintype_prod_eq_pow ι fun x : ℂ => Real.exp (- ‖x‖ ^ p),
Complex.integral_exp_neg_rpow hp]
· rw [finrank_pi_fintype, Complex.finrank_real_complex, Finset.sum_const, smul_eq_mul,
Nat.cast_mul, Nat.cast_ofNat, Fintype.card, mul_comm] |
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Order.Interval.Set.OrdConnectedComponent
import Mathlib.Topology.Order.Basic
import Mathlib.Topology.Separation.Regular
/-!
# Linear order is a completely normal Hausdorff topological space
In this file we prove that a linear order with order topology is a completely normal Hausdorff
topological space.
-/
open Filter Set Function OrderDual Topology Interval
variable {X : Type*} [LinearOrder X] [TopologicalSpace X] [OrderTopology X] {a : X} {s t : Set X}
namespace Set
@[simp]
theorem ordConnectedComponent_mem_nhds : ordConnectedComponent s a ∈ 𝓝 a ↔ s ∈ 𝓝 a := by
refine ⟨fun h => mem_of_superset h ordConnectedComponent_subset, fun h => ?_⟩
rcases exists_Icc_mem_subset_of_mem_nhds h with ⟨b, c, ha, ha', hs⟩
exact mem_of_superset ha' (subset_ordConnectedComponent ha hs)
theorem compl_ordConnectedSection_ordSeparatingSet_mem_nhdsGE (hd : Disjoint s (closure t))
(ha : a ∈ s) : (ordConnectedSection (ordSeparatingSet s t))ᶜ ∈ 𝓝[≥] a := by
have hmem : tᶜ ∈ 𝓝[≥] a := by
refine mem_nhdsWithin_of_mem_nhds ?_
rw [← mem_interior_iff_mem_nhds, interior_compl]
exact disjoint_left.1 hd ha
rcases exists_Icc_mem_subset_of_mem_nhdsGE hmem with ⟨b, hab, hmem', hsub⟩
by_cases H : Disjoint (Icc a b) (ordConnectedSection <| ordSeparatingSet s t)
· exact mem_of_superset hmem' (disjoint_left.1 H)
· simp only [Set.disjoint_left, not_forall, Classical.not_not] at H
rcases H with ⟨c, ⟨hac, hcb⟩, hc⟩
have hsub' : Icc a b ⊆ ordConnectedComponent tᶜ a :=
subset_ordConnectedComponent (left_mem_Icc.2 hab) hsub
have hd : Disjoint s (ordConnectedSection (ordSeparatingSet s t)) :=
disjoint_left_ordSeparatingSet.mono_right ordConnectedSection_subset
replace hac : a < c := hac.lt_of_ne <| Ne.symm <| ne_of_mem_of_not_mem hc <|
disjoint_left.1 hd ha
filter_upwards [Ico_mem_nhdsGE hac] with x hx hx'
refine hx.2.ne (eq_of_mem_ordConnectedSection_of_uIcc_subset hx' hc ?_)
refine subset_inter (subset_iUnion₂_of_subset a ha ?_) ?_
· exact OrdConnected.uIcc_subset inferInstance (hsub' ⟨hx.1, hx.2.le.trans hcb⟩)
(hsub' ⟨hac.le, hcb⟩)
· rcases mem_iUnion₂.1 (ordConnectedSection_subset hx').2 with ⟨y, hyt, hxy⟩
refine subset_iUnion₂_of_subset y hyt (OrdConnected.uIcc_subset inferInstance hxy ?_)
refine subset_ordConnectedComponent left_mem_uIcc hxy ?_
suffices c < y by
rw [uIcc_of_ge (hx.2.trans this).le]
exact ⟨hx.2.le, this.le⟩
refine lt_of_not_le fun hyc => ?_
have hya : y < a := not_le.1 fun hay => hsub ⟨hay, hyc.trans hcb⟩ hyt
exact hxy (Icc_subset_uIcc ⟨hya.le, hx.1⟩) ha
@[deprecated (since := "2024-12-22")]
alias compl_section_ordSeparatingSet_mem_nhdsWithin_Ici :=
compl_ordConnectedSection_ordSeparatingSet_mem_nhdsGE
| Mathlib/Topology/Order/T5.lean | 66 | 71 | theorem compl_ordConnectedSection_ordSeparatingSet_mem_nhdsLE (hd : Disjoint s (closure t))
(ha : a ∈ s) : (ordConnectedSection <| ordSeparatingSet s t)ᶜ ∈ 𝓝[≤] a := by | have hd' : Disjoint (ofDual ⁻¹' s) (closure <| ofDual ⁻¹' t) := hd
have ha' : toDual a ∈ ofDual ⁻¹' s := ha
simpa only [dual_ordSeparatingSet, dual_ordConnectedSection] using
compl_ordConnectedSection_ordSeparatingSet_mem_nhdsGE hd' ha' |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Kim Morrison, Jens Wagemaker, Johan Commelin
-/
import Mathlib.Algebra.Polynomial.BigOperators
import Mathlib.Algebra.Polynomial.RingDivision
import Mathlib.Data.Set.Finite.Lemmas
import Mathlib.RingTheory.Coprime.Lemmas
import Mathlib.RingTheory.Localization.FractionRing
import Mathlib.SetTheory.Cardinal.Order
/-!
# Theory of univariate polynomials
We define the multiset of roots of a polynomial, and prove basic results about it.
## Main definitions
* `Polynomial.roots p`: The multiset containing all the roots of `p`, including their
multiplicities.
* `Polynomial.rootSet p E`: The set of distinct roots of `p` in an algebra `E`.
## Main statements
* `Polynomial.C_leadingCoeff_mul_prod_multiset_X_sub_C`: If a polynomial has as many roots as its
degree, it can be written as the product of its leading coefficient with `∏ (X - a)` where `a`
ranges through its roots.
-/
assert_not_exists Ideal
open Multiset Finset
noncomputable section
namespace Polynomial
universe u v w z
variable {R : Type u} {S : Type v} {T : Type w} {a b : R} {n : ℕ}
section CommRing
variable [CommRing R] [IsDomain R] {p q : R[X]}
section Roots
/-- `roots p` noncomputably gives a multiset containing all the roots of `p`,
including their multiplicities. -/
noncomputable def roots (p : R[X]) : Multiset R :=
haveI := Classical.decEq R
haveI := Classical.dec (p = 0)
if h : p = 0 then ∅ else Classical.choose (exists_multiset_roots h)
theorem roots_def [DecidableEq R] (p : R[X]) [Decidable (p = 0)] :
p.roots = if h : p = 0 then ∅ else Classical.choose (exists_multiset_roots h) := by
rename_i iR ip0
obtain rfl := Subsingleton.elim iR (Classical.decEq R)
obtain rfl := Subsingleton.elim ip0 (Classical.dec (p = 0))
rfl
@[simp]
theorem roots_zero : (0 : R[X]).roots = 0 :=
dif_pos rfl
theorem card_roots (hp0 : p ≠ 0) : (Multiset.card (roots p) : WithBot ℕ) ≤ degree p := by
classical
unfold roots
rw [dif_neg hp0]
exact (Classical.choose_spec (exists_multiset_roots hp0)).1
theorem card_roots' (p : R[X]) : Multiset.card p.roots ≤ natDegree p := by
by_cases hp0 : p = 0
· simp [hp0]
exact WithBot.coe_le_coe.1 (le_trans (card_roots hp0) (le_of_eq <| degree_eq_natDegree hp0))
theorem card_roots_sub_C {p : R[X]} {a : R} (hp0 : 0 < degree p) :
(Multiset.card (p - C a).roots : WithBot ℕ) ≤ degree p :=
calc
(Multiset.card (p - C a).roots : WithBot ℕ) ≤ degree (p - C a) :=
card_roots <| mt sub_eq_zero.1 fun h => not_le_of_gt hp0 <| h.symm ▸ degree_C_le
_ = degree p := by rw [sub_eq_add_neg, ← C_neg]; exact degree_add_C hp0
theorem card_roots_sub_C' {p : R[X]} {a : R} (hp0 : 0 < degree p) :
Multiset.card (p - C a).roots ≤ natDegree p :=
WithBot.coe_le_coe.1
(le_trans (card_roots_sub_C hp0)
(le_of_eq <| degree_eq_natDegree fun h => by simp_all [lt_irrefl]))
@[simp]
theorem count_roots [DecidableEq R] (p : R[X]) : p.roots.count a = rootMultiplicity a p := by
classical
by_cases hp : p = 0
· simp [hp]
rw [roots_def, dif_neg hp]
exact (Classical.choose_spec (exists_multiset_roots hp)).2 a
@[simp]
theorem mem_roots' : a ∈ p.roots ↔ p ≠ 0 ∧ IsRoot p a := by
classical
rw [← count_pos, count_roots p, rootMultiplicity_pos']
theorem mem_roots (hp : p ≠ 0) : a ∈ p.roots ↔ IsRoot p a :=
mem_roots'.trans <| and_iff_right hp
theorem ne_zero_of_mem_roots (h : a ∈ p.roots) : p ≠ 0 :=
(mem_roots'.1 h).1
theorem isRoot_of_mem_roots (h : a ∈ p.roots) : IsRoot p a :=
(mem_roots'.1 h).2
theorem mem_roots_map_of_injective [Semiring S] {p : S[X]} {f : S →+* R}
(hf : Function.Injective f) {x : R} (hp : p ≠ 0) : x ∈ (p.map f).roots ↔ p.eval₂ f x = 0 := by
rw [mem_roots ((Polynomial.map_ne_zero_iff hf).mpr hp), IsRoot, eval_map]
lemma mem_roots_iff_aeval_eq_zero {x : R} (w : p ≠ 0) : x ∈ roots p ↔ aeval x p = 0 := by
rw [aeval_def, ← mem_roots_map_of_injective (FaithfulSMul.algebraMap_injective _ _) w,
Algebra.id.map_eq_id, map_id]
theorem card_le_degree_of_subset_roots {p : R[X]} {Z : Finset R} (h : Z.val ⊆ p.roots) :
#Z ≤ p.natDegree :=
(Multiset.card_le_card (Finset.val_le_iff_val_subset.2 h)).trans (Polynomial.card_roots' p)
theorem finite_setOf_isRoot {p : R[X]} (hp : p ≠ 0) : Set.Finite { x | IsRoot p x } := by
classical
simpa only [← Finset.setOf_mem, Multiset.mem_toFinset, mem_roots hp]
using p.roots.toFinset.finite_toSet
theorem eq_zero_of_infinite_isRoot (p : R[X]) (h : Set.Infinite { x | IsRoot p x }) : p = 0 :=
not_imp_comm.mp finite_setOf_isRoot h
theorem exists_max_root [LinearOrder R] (p : R[X]) (hp : p ≠ 0) : ∃ x₀, ∀ x, p.IsRoot x → x ≤ x₀ :=
Set.exists_upper_bound_image _ _ <| finite_setOf_isRoot hp
theorem exists_min_root [LinearOrder R] (p : R[X]) (hp : p ≠ 0) : ∃ x₀, ∀ x, p.IsRoot x → x₀ ≤ x :=
Set.exists_lower_bound_image _ _ <| finite_setOf_isRoot hp
theorem eq_of_infinite_eval_eq (p q : R[X]) (h : Set.Infinite { x | eval x p = eval x q }) :
p = q := by
rw [← sub_eq_zero]
apply eq_zero_of_infinite_isRoot
simpa only [IsRoot, eval_sub, sub_eq_zero]
theorem roots_mul {p q : R[X]} (hpq : p * q ≠ 0) : (p * q).roots = p.roots + q.roots := by
classical
exact Multiset.ext.mpr fun r => by
rw [count_add, count_roots, count_roots, count_roots, rootMultiplicity_mul hpq]
theorem roots.le_of_dvd (h : q ≠ 0) : p ∣ q → roots p ≤ roots q := by
rintro ⟨k, rfl⟩
exact Multiset.le_iff_exists_add.mpr ⟨k.roots, roots_mul h⟩
theorem mem_roots_sub_C' {p : R[X]} {a x : R} : x ∈ (p - C a).roots ↔ p ≠ C a ∧ p.eval x = a := by
rw [mem_roots', IsRoot.def, sub_ne_zero, eval_sub, sub_eq_zero, eval_C]
theorem mem_roots_sub_C {p : R[X]} {a x : R} (hp0 : 0 < degree p) :
x ∈ (p - C a).roots ↔ p.eval x = a :=
mem_roots_sub_C'.trans <| and_iff_right fun hp => hp0.not_le <| hp.symm ▸ degree_C_le
@[simp]
theorem roots_X_sub_C (r : R) : roots (X - C r) = {r} := by
classical
ext s
rw [count_roots, rootMultiplicity_X_sub_C, count_singleton]
@[simp]
theorem roots_X_add_C (r : R) : roots (X + C r) = {-r} := by simpa using roots_X_sub_C (-r)
@[simp]
theorem roots_X : roots (X : R[X]) = {0} := by rw [← roots_X_sub_C, C_0, sub_zero]
@[simp]
theorem roots_C (x : R) : (C x).roots = 0 := by
classical exact
if H : x = 0 then by rw [H, C_0, roots_zero]
else
Multiset.ext.mpr fun r => (by
rw [count_roots, count_zero, rootMultiplicity_eq_zero (not_isRoot_C _ _ H)])
@[simp]
theorem roots_one : (1 : R[X]).roots = ∅ :=
roots_C 1
@[simp]
theorem roots_C_mul (p : R[X]) (ha : a ≠ 0) : (C a * p).roots = p.roots := by
by_cases hp : p = 0 <;>
simp only [roots_mul, *, Ne, mul_eq_zero, C_eq_zero, or_self_iff, not_false_iff, roots_C,
zero_add, mul_zero]
@[simp]
theorem roots_smul_nonzero (p : R[X]) (ha : a ≠ 0) : (a • p).roots = p.roots := by
rw [smul_eq_C_mul, roots_C_mul _ ha]
@[simp]
lemma roots_neg (p : R[X]) : (-p).roots = p.roots := by
rw [← neg_one_smul R p, roots_smul_nonzero p (neg_ne_zero.mpr one_ne_zero)]
@[simp]
theorem roots_C_mul_X_sub_C_of_IsUnit (b : R) (a : Rˣ) : (C (a : R) * X - C b).roots =
{a⁻¹ * b} := by
rw [← roots_C_mul _ (Units.ne_zero a⁻¹), mul_sub, ← mul_assoc, ← C_mul, ← C_mul,
Units.inv_mul, C_1, one_mul]
exact roots_X_sub_C (a⁻¹ * b)
@[simp]
theorem roots_C_mul_X_add_C_of_IsUnit (b : R) (a : Rˣ) : (C (a : R) * X + C b).roots =
{-(a⁻¹ * b)} := by
rw [← sub_neg_eq_add, ← C_neg, roots_C_mul_X_sub_C_of_IsUnit, mul_neg]
theorem roots_list_prod (L : List R[X]) :
(0 : R[X]) ∉ L → L.prod.roots = (L : Multiset R[X]).bind roots :=
List.recOn L (fun _ => roots_one) fun hd tl ih H => by
rw [List.mem_cons, not_or] at H
rw [List.prod_cons, roots_mul (mul_ne_zero (Ne.symm H.1) <| List.prod_ne_zero H.2), ←
Multiset.cons_coe, Multiset.cons_bind, ih H.2]
theorem roots_multiset_prod (m : Multiset R[X]) : (0 : R[X]) ∉ m → m.prod.roots = m.bind roots := by
rcases m with ⟨L⟩
simpa only [Multiset.prod_coe, quot_mk_to_coe''] using roots_list_prod L
theorem roots_prod {ι : Type*} (f : ι → R[X]) (s : Finset ι) :
s.prod f ≠ 0 → (s.prod f).roots = s.val.bind fun i => roots (f i) := by
rcases s with ⟨m, hm⟩
simpa [Multiset.prod_eq_zero_iff, Multiset.bind_map] using roots_multiset_prod (m.map f)
@[simp]
theorem roots_pow (p : R[X]) (n : ℕ) : (p ^ n).roots = n • p.roots := by
induction n with
| zero => rw [pow_zero, roots_one, zero_smul, empty_eq_zero]
| succ n ihn =>
rcases eq_or_ne p 0 with (rfl | hp)
· rw [zero_pow n.succ_ne_zero, roots_zero, smul_zero]
· rw [pow_succ, roots_mul (mul_ne_zero (pow_ne_zero _ hp) hp), ihn, add_smul, one_smul]
theorem roots_X_pow (n : ℕ) : (X ^ n : R[X]).roots = n • ({0} : Multiset R) := by
rw [roots_pow, roots_X]
theorem roots_C_mul_X_pow (ha : a ≠ 0) (n : ℕ) :
Polynomial.roots (C a * X ^ n) = n • ({0} : Multiset R) := by
rw [roots_C_mul _ ha, roots_X_pow]
@[simp]
theorem roots_monomial (ha : a ≠ 0) (n : ℕ) : (monomial n a).roots = n • ({0} : Multiset R) := by
rw [← C_mul_X_pow_eq_monomial, roots_C_mul_X_pow ha]
theorem roots_prod_X_sub_C (s : Finset R) : (s.prod fun a => X - C a).roots = s.val := by
apply (roots_prod (fun a => X - C a) s ?_).trans
· simp_rw [roots_X_sub_C]
rw [Multiset.bind_singleton, Multiset.map_id']
· refine prod_ne_zero_iff.mpr (fun a _ => X_sub_C_ne_zero a)
@[simp]
theorem roots_multiset_prod_X_sub_C (s : Multiset R) : (s.map fun a => X - C a).prod.roots = s := by
rw [roots_multiset_prod, Multiset.bind_map]
· simp_rw [roots_X_sub_C]
rw [Multiset.bind_singleton, Multiset.map_id']
· rw [Multiset.mem_map]
rintro ⟨a, -, h⟩
exact X_sub_C_ne_zero a h
theorem card_roots_X_pow_sub_C {n : ℕ} (hn : 0 < n) (a : R) :
Multiset.card (roots ((X : R[X]) ^ n - C a)) ≤ n :=
WithBot.coe_le_coe.1 <|
calc
(Multiset.card (roots ((X : R[X]) ^ n - C a)) : WithBot ℕ) ≤ degree ((X : R[X]) ^ n - C a) :=
card_roots (X_pow_sub_C_ne_zero hn a)
_ = n := degree_X_pow_sub_C hn a
section NthRoots
/-- `nthRoots n a` noncomputably returns the solutions to `x ^ n = a`. -/
def nthRoots (n : ℕ) (a : R) : Multiset R :=
roots ((X : R[X]) ^ n - C a)
@[simp]
theorem mem_nthRoots {n : ℕ} (hn : 0 < n) {a x : R} : x ∈ nthRoots n a ↔ x ^ n = a := by
rw [nthRoots, mem_roots (X_pow_sub_C_ne_zero hn a), IsRoot.def, eval_sub, eval_C, eval_pow,
eval_X, sub_eq_zero]
@[simp]
theorem nthRoots_zero (r : R) : nthRoots 0 r = 0 := by
simp only [empty_eq_zero, pow_zero, nthRoots, ← C_1, ← C_sub, roots_C]
@[simp]
theorem nthRoots_zero_right {R} [CommRing R] [IsDomain R] (n : ℕ) :
nthRoots n (0 : R) = Multiset.replicate n 0 := by
rw [nthRoots, C.map_zero, sub_zero, roots_pow, roots_X, Multiset.nsmul_singleton]
theorem card_nthRoots (n : ℕ) (a : R) : Multiset.card (nthRoots n a) ≤ n := by
classical exact
(if hn : n = 0 then
if h : (X : R[X]) ^ n - C a = 0 then by
simp [Nat.zero_le, nthRoots, roots, h, dif_pos rfl, empty_eq_zero, Multiset.card_zero]
else
WithBot.coe_le_coe.1
(le_trans (card_roots h)
(by
rw [hn, pow_zero, ← C_1, ← RingHom.map_sub]
exact degree_C_le))
else by
rw [← Nat.cast_le (α := WithBot ℕ)]
rw [← degree_X_pow_sub_C (Nat.pos_of_ne_zero hn) a]
exact card_roots (X_pow_sub_C_ne_zero (Nat.pos_of_ne_zero hn) a))
@[simp]
theorem nthRoots_two_eq_zero_iff {r : R} : nthRoots 2 r = 0 ↔ ¬IsSquare r := by
simp_rw [isSquare_iff_exists_sq, eq_zero_iff_forall_not_mem, mem_nthRoots (by norm_num : 0 < 2),
← not_exists, eq_comm]
/-- The multiset `nthRoots ↑n a` as a Finset. Previously `nthRootsFinset n` was defined to be
`nthRoots n (1 : R)` as a Finset. That situation can be recovered by setting `a` to be `(1 : R)` -/
def nthRootsFinset (n : ℕ) {R : Type*} (a : R) [CommRing R] [IsDomain R] : Finset R :=
haveI := Classical.decEq R
Multiset.toFinset (nthRoots n a)
lemma nthRootsFinset_def (n : ℕ) {R : Type*} (a : R) [CommRing R] [IsDomain R] [DecidableEq R] :
nthRootsFinset n a = Multiset.toFinset (nthRoots n a) := by
unfold nthRootsFinset
convert rfl
@[simp]
| Mathlib/Algebra/Polynomial/Roots.lean | 324 | 338 | theorem mem_nthRootsFinset {n : ℕ} (h : 0 < n) (a : R) {x : R} :
x ∈ nthRootsFinset n a ↔ x ^ (n : ℕ) = a := by | classical
rw [nthRootsFinset_def, mem_toFinset, mem_nthRoots h]
@[simp]
theorem nthRootsFinset_zero (a : R) : nthRootsFinset 0 a = ∅ := by
classical simp [nthRootsFinset_def]
theorem map_mem_nthRootsFinset {S F : Type*} [CommRing S] [IsDomain S] [FunLike F R S]
[MonoidHomClass F R S] {a : R} {x : R} (hx : x ∈ nthRootsFinset n a) (f : F) :
f x ∈ nthRootsFinset n (f a) := by
by_cases hn : n = 0
· simp [hn] at hx
· rw [mem_nthRootsFinset <| Nat.pos_of_ne_zero hn, ← map_pow, (mem_nthRootsFinset |
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Algebra.Operations
import Mathlib.Algebra.Module.BigOperators
import Mathlib.Data.Fintype.Lattice
import Mathlib.RingTheory.Coprime.Lemmas
import Mathlib.RingTheory.Ideal.Basic
import Mathlib.RingTheory.NonUnitalSubsemiring.Basic
/-!
# More operations on modules and ideals
-/
assert_not_exists Basis -- See `RingTheory.Ideal.Basis`
Submodule.hasQuotient -- See `RingTheory.Ideal.Quotient.Operations`
universe u v w x
open Pointwise
namespace Submodule
lemma coe_span_smul {R' M' : Type*} [CommSemiring R'] [AddCommMonoid M'] [Module R' M']
(s : Set R') (N : Submodule R' M') :
(Ideal.span s : Set R') • N = s • N :=
set_smul_eq_of_le _ _ _
(by rintro r n hr hn
induction hr using Submodule.span_induction with
| mem _ h => exact mem_set_smul_of_mem_mem h hn
| zero => rw [zero_smul]; exact Submodule.zero_mem _
| add _ _ _ _ ihr ihs => rw [add_smul]; exact Submodule.add_mem _ ihr ihs
| smul _ _ hr =>
rw [mem_span_set] at hr
obtain ⟨c, hc, rfl⟩ := hr
rw [Finsupp.sum, Finset.smul_sum, Finset.sum_smul]
refine Submodule.sum_mem _ fun i hi => ?_
rw [← mul_smul, smul_eq_mul, mul_comm, mul_smul]
exact mem_set_smul_of_mem_mem (hc hi) <| Submodule.smul_mem _ _ hn) <|
set_smul_mono_left _ Submodule.subset_span
lemma span_singleton_toAddSubgroup_eq_zmultiples (a : ℤ) :
(span ℤ {a}).toAddSubgroup = AddSubgroup.zmultiples a := by
ext i
simp [Ideal.mem_span_singleton', AddSubgroup.mem_zmultiples_iff]
@[simp] lemma _root_.Ideal.span_singleton_toAddSubgroup_eq_zmultiples (a : ℤ) :
(Ideal.span {a}).toAddSubgroup = AddSubgroup.zmultiples a :=
Submodule.span_singleton_toAddSubgroup_eq_zmultiples _
variable {R : Type u} {M : Type v} {M' F G : Type*}
section Semiring
variable [Semiring R] [AddCommMonoid M] [Module R M]
/-- This duplicates the global `smul_eq_mul`, but doesn't have to unfold anywhere near as much to
apply. -/
protected theorem _root_.Ideal.smul_eq_mul (I J : Ideal R) : I • J = I * J :=
rfl
variable {I J : Ideal R} {N : Submodule R M}
theorem smul_le_right : I • N ≤ N :=
smul_le.2 fun r _ _ ↦ N.smul_mem r
theorem map_le_smul_top (I : Ideal R) (f : R →ₗ[R] M) :
Submodule.map f I ≤ I • (⊤ : Submodule R M) := by
rintro _ ⟨y, hy, rfl⟩
rw [← mul_one y, ← smul_eq_mul, f.map_smul]
exact smul_mem_smul hy mem_top
variable (I J N)
@[simp]
theorem top_smul : (⊤ : Ideal R) • N = N :=
le_antisymm smul_le_right fun r hri => one_smul R r ▸ smul_mem_smul mem_top hri
protected theorem mul_smul : (I * J) • N = I • J • N :=
Submodule.smul_assoc _ _ _
theorem mem_of_span_top_of_smul_mem (M' : Submodule R M) (s : Set R) (hs : Ideal.span s = ⊤) (x : M)
(H : ∀ r : s, (r : R) • x ∈ M') : x ∈ M' := by
suffices LinearMap.range (LinearMap.toSpanSingleton R M x) ≤ M' by
rw [← LinearMap.toSpanSingleton_one R M x]
exact this (LinearMap.mem_range_self _ 1)
rw [LinearMap.range_eq_map, ← hs, map_le_iff_le_comap, Ideal.span, span_le]
exact fun r hr ↦ H ⟨r, hr⟩
variable {M' : Type w} [AddCommMonoid M'] [Module R M']
@[simp]
theorem map_smul'' (f : M →ₗ[R] M') : (I • N).map f = I • N.map f :=
le_antisymm
(map_le_iff_le_comap.2 <|
smul_le.2 fun r hr n hn =>
show f (r • n) ∈ I • N.map f from
(f.map_smul r n).symm ▸ smul_mem_smul hr (mem_map_of_mem hn)) <|
smul_le.2 fun r hr _ hn =>
let ⟨p, hp, hfp⟩ := mem_map.1 hn
hfp ▸ f.map_smul r p ▸ mem_map_of_mem (smul_mem_smul hr hp)
theorem mem_smul_top_iff (N : Submodule R M) (x : N) :
x ∈ I • (⊤ : Submodule R N) ↔ (x : M) ∈ I • N := by
have : Submodule.map N.subtype (I • ⊤) = I • N := by
rw [Submodule.map_smul'', Submodule.map_top, Submodule.range_subtype]
simp [← this, -map_smul'']
@[simp]
theorem smul_comap_le_comap_smul (f : M →ₗ[R] M') (S : Submodule R M') (I : Ideal R) :
I • S.comap f ≤ (I • S).comap f := by
refine Submodule.smul_le.mpr fun r hr x hx => ?_
rw [Submodule.mem_comap] at hx ⊢
rw [f.map_smul]
exact Submodule.smul_mem_smul hr hx
end Semiring
section CommSemiring
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid M'] [Module R M']
open Pointwise
theorem mem_smul_span_singleton {I : Ideal R} {m : M} {x : M} :
x ∈ I • span R ({m} : Set M) ↔ ∃ y ∈ I, y • m = x :=
⟨fun hx =>
smul_induction_on hx
(fun r hri _ hnm =>
let ⟨s, hs⟩ := mem_span_singleton.1 hnm
⟨r * s, I.mul_mem_right _ hri, hs ▸ mul_smul r s m⟩)
fun m1 m2 ⟨y1, hyi1, hy1⟩ ⟨y2, hyi2, hy2⟩ =>
⟨y1 + y2, I.add_mem hyi1 hyi2, by rw [add_smul, hy1, hy2]⟩,
fun ⟨_, hyi, hy⟩ => hy ▸ smul_mem_smul hyi (subset_span <| Set.mem_singleton m)⟩
variable {I J : Ideal R} {N P : Submodule R M}
variable (S : Set R) (T : Set M)
theorem smul_eq_map₂ : I • N = Submodule.map₂ (LinearMap.lsmul R M) I N :=
le_antisymm (smul_le.mpr fun _m hm _n ↦ Submodule.apply_mem_map₂ _ hm)
(map₂_le.mpr fun _m hm _n ↦ smul_mem_smul hm)
theorem span_smul_span : Ideal.span S • span R T = span R (⋃ (s ∈ S) (t ∈ T), {s • t}) := by
rw [smul_eq_map₂]
exact (map₂_span_span _ _ _ _).trans <| congr_arg _ <| Set.image2_eq_iUnion _ _ _
theorem ideal_span_singleton_smul (r : R) (N : Submodule R M) :
(Ideal.span {r} : Ideal R) • N = r • N := by
have : span R (⋃ (t : M) (_ : t ∈ N), {r • t}) = r • N := by
convert span_eq (r • N)
exact (Set.image_eq_iUnion _ (N : Set M)).symm
conv_lhs => rw [← span_eq N, span_smul_span]
simpa
/-- Given `s`, a generating set of `R`, to check that an `x : M` falls in a
submodule `M'` of `x`, we only need to show that `r ^ n • x ∈ M'` for some `n` for each `r : s`. -/
theorem mem_of_span_eq_top_of_smul_pow_mem (M' : Submodule R M) (s : Set R) (hs : Ideal.span s = ⊤)
(x : M) (H : ∀ r : s, ∃ n : ℕ, ((r : R) ^ n : R) • x ∈ M') : x ∈ M' := by
choose f hf using H
apply M'.mem_of_span_top_of_smul_mem _ (Ideal.span_range_pow_eq_top s hs f)
rintro ⟨_, r, hr, rfl⟩
exact hf r
open Pointwise in
@[simp]
theorem map_pointwise_smul (r : R) (N : Submodule R M) (f : M →ₗ[R] M') :
(r • N).map f = r • N.map f := by
simp_rw [← ideal_span_singleton_smul, map_smul'']
theorem mem_smul_span {s : Set M} {x : M} :
x ∈ I • Submodule.span R s ↔ x ∈ Submodule.span R (⋃ (a ∈ I) (b ∈ s), ({a • b} : Set M)) := by
rw [← I.span_eq, Submodule.span_smul_span, I.span_eq]
simp
variable (I)
/-- If `x` is an `I`-multiple of the submodule spanned by `f '' s`,
then we can write `x` as an `I`-linear combination of the elements of `f '' s`. -/
theorem mem_ideal_smul_span_iff_exists_sum {ι : Type*} (f : ι → M) (x : M) :
x ∈ I • span R (Set.range f) ↔
∃ (a : ι →₀ R) (_ : ∀ i, a i ∈ I), (a.sum fun i c => c • f i) = x := by
constructor; swap
· rintro ⟨a, ha, rfl⟩
exact Submodule.sum_mem _ fun c _ => smul_mem_smul (ha c) <| subset_span <| Set.mem_range_self _
refine fun hx => span_induction ?_ ?_ ?_ ?_ (mem_smul_span.mp hx)
· simp only [Set.mem_iUnion, Set.mem_range, Set.mem_singleton_iff]
rintro x ⟨y, hy, x, ⟨i, rfl⟩, rfl⟩
refine ⟨Finsupp.single i y, fun j => ?_, ?_⟩
· letI := Classical.decEq ι
rw [Finsupp.single_apply]
split_ifs
· assumption
· exact I.zero_mem
refine @Finsupp.sum_single_index ι R M _ _ i _ (fun i y => y • f i) ?_
simp
· exact ⟨0, fun _ => I.zero_mem, Finsupp.sum_zero_index⟩
· rintro x y - - ⟨ax, hax, rfl⟩ ⟨ay, hay, rfl⟩
refine ⟨ax + ay, fun i => I.add_mem (hax i) (hay i), Finsupp.sum_add_index' ?_ ?_⟩ <;>
intros <;> simp only [zero_smul, add_smul]
· rintro c x - ⟨a, ha, rfl⟩
refine ⟨c • a, fun i => I.mul_mem_left c (ha i), ?_⟩
rw [Finsupp.sum_smul_index, Finsupp.smul_sum] <;> intros <;> simp only [zero_smul, mul_smul]
theorem mem_ideal_smul_span_iff_exists_sum' {ι : Type*} (s : Set ι) (f : ι → M) (x : M) :
x ∈ I • span R (f '' s) ↔
∃ (a : s →₀ R) (_ : ∀ i, a i ∈ I), (a.sum fun i c => c • f i) = x := by
rw [← Submodule.mem_ideal_smul_span_iff_exists_sum, ← Set.image_eq_range]
end CommSemiring
end Submodule
namespace Ideal
section Add
variable {R : Type u} [Semiring R]
@[simp]
theorem add_eq_sup {I J : Ideal R} : I + J = I ⊔ J :=
rfl
@[simp]
theorem zero_eq_bot : (0 : Ideal R) = ⊥ :=
rfl
@[simp]
theorem sum_eq_sup {ι : Type*} (s : Finset ι) (f : ι → Ideal R) : s.sum f = s.sup f :=
rfl
end Add
section Semiring
variable {R : Type u} [Semiring R] {I J K L : Ideal R}
@[simp]
theorem one_eq_top : (1 : Ideal R) = ⊤ := by
rw [Submodule.one_eq_span, ← Ideal.span, Ideal.span_singleton_one]
theorem add_eq_one_iff : I + J = 1 ↔ ∃ i ∈ I, ∃ j ∈ J, i + j = 1 := by
rw [one_eq_top, eq_top_iff_one, add_eq_sup, Submodule.mem_sup]
theorem mul_mem_mul {r s} (hr : r ∈ I) (hs : s ∈ J) : r * s ∈ I * J :=
Submodule.smul_mem_smul hr hs
theorem pow_mem_pow {x : R} (hx : x ∈ I) (n : ℕ) : x ^ n ∈ I ^ n :=
Submodule.pow_mem_pow _ hx _
theorem mul_le : I * J ≤ K ↔ ∀ r ∈ I, ∀ s ∈ J, r * s ∈ K :=
Submodule.smul_le
theorem mul_le_left : I * J ≤ J :=
mul_le.2 fun _ _ _ => J.mul_mem_left _
@[simp]
theorem sup_mul_left_self : I ⊔ J * I = I :=
sup_eq_left.2 mul_le_left
@[simp]
theorem mul_left_self_sup : J * I ⊔ I = I :=
sup_eq_right.2 mul_le_left
theorem mul_le_right [I.IsTwoSided] : I * J ≤ I :=
mul_le.2 fun _ hr _ _ ↦ I.mul_mem_right _ hr
@[simp]
theorem sup_mul_right_self [I.IsTwoSided] : I ⊔ I * J = I :=
sup_eq_left.2 mul_le_right
@[simp]
theorem mul_right_self_sup [I.IsTwoSided] : I * J ⊔ I = I :=
sup_eq_right.2 mul_le_right
protected theorem mul_assoc : I * J * K = I * (J * K) :=
Submodule.smul_assoc I J K
variable (I)
theorem mul_bot : I * ⊥ = ⊥ := by simp
theorem bot_mul : ⊥ * I = ⊥ := by simp
@[simp]
theorem top_mul : ⊤ * I = I :=
Submodule.top_smul I
variable {I}
theorem mul_mono (hik : I ≤ K) (hjl : J ≤ L) : I * J ≤ K * L :=
Submodule.smul_mono hik hjl
theorem mul_mono_left (h : I ≤ J) : I * K ≤ J * K :=
Submodule.smul_mono_left h
theorem mul_mono_right (h : J ≤ K) : I * J ≤ I * K :=
smul_mono_right I h
variable (I J K)
theorem mul_sup : I * (J ⊔ K) = I * J ⊔ I * K :=
Submodule.smul_sup I J K
theorem sup_mul : (I ⊔ J) * K = I * K ⊔ J * K :=
Submodule.sup_smul I J K
variable {I J K}
theorem pow_le_pow_right {m n : ℕ} (h : m ≤ n) : I ^ n ≤ I ^ m := by
obtain _ | m := m
· rw [Submodule.pow_zero, one_eq_top]; exact le_top
obtain ⟨n, rfl⟩ := Nat.exists_eq_add_of_le h
rw [add_comm, Submodule.pow_add _ m.add_one_ne_zero]
exact mul_le_left
theorem pow_le_self {n : ℕ} (hn : n ≠ 0) : I ^ n ≤ I :=
calc
I ^ n ≤ I ^ 1 := pow_le_pow_right (Nat.pos_of_ne_zero hn)
_ = I := Submodule.pow_one _
theorem pow_right_mono (e : I ≤ J) (n : ℕ) : I ^ n ≤ J ^ n := by
induction' n with _ hn
· rw [Submodule.pow_zero, Submodule.pow_zero]
· rw [Submodule.pow_succ, Submodule.pow_succ]
exact Ideal.mul_mono hn e
namespace IsTwoSided
instance (priority := low) [J.IsTwoSided] : (I * J).IsTwoSided :=
⟨fun b ha ↦ Submodule.mul_induction_on ha
(fun i hi j hj ↦ by rw [mul_assoc]; exact mul_mem_mul hi (mul_mem_right _ _ hj))
fun x y hx hy ↦ by rw [right_distrib]; exact add_mem hx hy⟩
variable [I.IsTwoSided] (m n : ℕ)
instance (priority := low) : (I ^ n).IsTwoSided :=
n.rec
(by rw [Submodule.pow_zero, one_eq_top]; infer_instance)
(fun _ _ ↦ by rw [Submodule.pow_succ]; infer_instance)
protected theorem mul_one : I * 1 = I :=
mul_le_right.antisymm
fun i hi ↦ mul_one i ▸ mul_mem_mul hi (one_eq_top (R := R) ▸ Submodule.mem_top)
protected theorem pow_add : I ^ (m + n) = I ^ m * I ^ n := by
obtain rfl | h := eq_or_ne n 0
· rw [add_zero, Submodule.pow_zero, IsTwoSided.mul_one]
· exact Submodule.pow_add _ h
protected theorem pow_succ : I ^ (n + 1) = I * I ^ n := by
rw [add_comm, IsTwoSided.pow_add, Submodule.pow_one]
end IsTwoSided
@[simp]
theorem mul_eq_bot [NoZeroDivisors R] : I * J = ⊥ ↔ I = ⊥ ∨ J = ⊥ :=
⟨fun hij =>
or_iff_not_imp_left.mpr fun I_ne_bot =>
J.eq_bot_iff.mpr fun j hj =>
let ⟨i, hi, ne0⟩ := I.ne_bot_iff.mp I_ne_bot
Or.resolve_left (mul_eq_zero.mp ((I * J).eq_bot_iff.mp hij _ (mul_mem_mul hi hj))) ne0,
fun h => by obtain rfl | rfl := h; exacts [bot_mul _, mul_bot _]⟩
instance [NoZeroDivisors R] : NoZeroDivisors (Ideal R) where
eq_zero_or_eq_zero_of_mul_eq_zero := mul_eq_bot.1
instance {S A : Type*} [Semiring S] [SMul R S] [AddCommMonoid A] [Module R A] [Module S A]
[IsScalarTower R S A] [NoZeroSMulDivisors R A] {I : Submodule S A} : NoZeroSMulDivisors R I :=
Submodule.noZeroSMulDivisors (Submodule.restrictScalars R I)
theorem pow_eq_zero_of_mem {I : Ideal R} {n m : ℕ} (hnI : I ^ n = 0) (hmn : n ≤ m) {x : R}
(hx : x ∈ I) : x ^ m = 0 := by
simpa [hnI] using pow_le_pow_right hmn <| pow_mem_pow hx m
end Semiring
section MulAndRadical
variable {R : Type u} {ι : Type*} [CommSemiring R]
variable {I J K L : Ideal R}
theorem mul_mem_mul_rev {r s} (hr : r ∈ I) (hs : s ∈ J) : s * r ∈ I * J :=
mul_comm r s ▸ mul_mem_mul hr hs
theorem prod_mem_prod {ι : Type*} {s : Finset ι} {I : ι → Ideal R} {x : ι → R} :
(∀ i ∈ s, x i ∈ I i) → (∏ i ∈ s, x i) ∈ ∏ i ∈ s, I i := by
classical
refine Finset.induction_on s ?_ ?_
· intro
rw [Finset.prod_empty, Finset.prod_empty, one_eq_top]
exact Submodule.mem_top
· intro a s ha IH h
rw [Finset.prod_insert ha, Finset.prod_insert ha]
exact
mul_mem_mul (h a <| Finset.mem_insert_self a s)
(IH fun i hi => h i <| Finset.mem_insert_of_mem hi)
lemma sup_pow_add_le_pow_sup_pow {n m : ℕ} : (I ⊔ J) ^ (n + m) ≤ I ^ n ⊔ J ^ m := by
rw [← Ideal.add_eq_sup, ← Ideal.add_eq_sup, add_pow, Ideal.sum_eq_sup]
apply Finset.sup_le
intros i hi
by_cases hn : n ≤ i
· exact (Ideal.mul_le_right.trans (Ideal.mul_le_right.trans
((Ideal.pow_le_pow_right hn).trans le_sup_left)))
· refine (Ideal.mul_le_right.trans (Ideal.mul_le_left.trans
((Ideal.pow_le_pow_right ?_).trans le_sup_right)))
omega
variable (I J K)
protected theorem mul_comm : I * J = J * I :=
le_antisymm (mul_le.2 fun _ hrI _ hsJ => mul_mem_mul_rev hsJ hrI)
(mul_le.2 fun _ hrJ _ hsI => mul_mem_mul_rev hsI hrJ)
theorem span_mul_span (S T : Set R) : span S * span T = span (⋃ (s ∈ S) (t ∈ T), {s * t}) :=
Submodule.span_smul_span S T
variable {I J K}
theorem span_mul_span' (S T : Set R) : span S * span T = span (S * T) := by
unfold span
rw [Submodule.span_mul_span]
theorem span_singleton_mul_span_singleton (r s : R) :
span {r} * span {s} = (span {r * s} : Ideal R) := by
unfold span
rw [Submodule.span_mul_span, Set.singleton_mul_singleton]
theorem span_singleton_pow (s : R) (n : ℕ) : span {s} ^ n = (span {s ^ n} : Ideal R) := by
induction' n with n ih; · simp [Set.singleton_one]
simp only [pow_succ, ih, span_singleton_mul_span_singleton]
theorem mem_mul_span_singleton {x y : R} {I : Ideal R} : x ∈ I * span {y} ↔ ∃ z ∈ I, z * y = x :=
Submodule.mem_smul_span_singleton
theorem mem_span_singleton_mul {x y : R} {I : Ideal R} : x ∈ span {y} * I ↔ ∃ z ∈ I, y * z = x := by
simp only [mul_comm, mem_mul_span_singleton]
theorem le_span_singleton_mul_iff {x : R} {I J : Ideal R} :
I ≤ span {x} * J ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI :=
show (∀ {zI} (_ : zI ∈ I), zI ∈ span {x} * J) ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zJ = zI by
simp only [mem_span_singleton_mul]
| Mathlib/RingTheory/Ideal/Operations.lean | 446 | 457 | theorem span_singleton_mul_le_iff {x : R} {I J : Ideal R} :
span {x} * I ≤ J ↔ ∀ z ∈ I, x * z ∈ J := by | simp only [mul_le, mem_span_singleton_mul, mem_span_singleton]
constructor
· intro h zI hzI
exact h x (dvd_refl x) zI hzI
· rintro h _ ⟨z, rfl⟩ zI hzI
rw [mul_comm x z, mul_assoc]
exact J.mul_mem_left _ (h zI hzI)
theorem span_singleton_mul_le_span_singleton_mul {x y : R} {I J : Ideal R} :
span {x} * I ≤ span {y} * J ↔ ∀ zI ∈ I, ∃ zJ ∈ J, x * zI = y * zJ := by |
/-
Copyright (c) 2021 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.ModelTheory.Ultraproducts
import Mathlib.ModelTheory.Bundled
import Mathlib.ModelTheory.Skolem
import Mathlib.Order.Filter.AtTopBot.Basic
/-!
# First-Order Satisfiability
This file deals with the satisfiability of first-order theories, as well as equivalence over them.
## Main Definitions
- `FirstOrder.Language.Theory.IsSatisfiable`: `T.IsSatisfiable` indicates that `T` has a nonempty
model.
- `FirstOrder.Language.Theory.IsFinitelySatisfiable`: `T.IsFinitelySatisfiable` indicates that
every finite subset of `T` is satisfiable.
- `FirstOrder.Language.Theory.IsComplete`: `T.IsComplete` indicates that `T` is satisfiable and
models each sentence or its negation.
- `Cardinal.Categorical`: A theory is `κ`-categorical if all models of size `κ` are isomorphic.
## Main Results
- The Compactness Theorem, `FirstOrder.Language.Theory.isSatisfiable_iff_isFinitelySatisfiable`,
shows that a theory is satisfiable iff it is finitely satisfiable.
- `FirstOrder.Language.completeTheory.isComplete`: The complete theory of a structure is
complete.
- `FirstOrder.Language.Theory.exists_large_model_of_infinite_model` shows that any theory with an
infinite model has arbitrarily large models.
- `FirstOrder.Language.Theory.exists_elementaryEmbedding_card_eq`: The Upward Löwenheim–Skolem
Theorem: If `κ` is a cardinal greater than the cardinalities of `L` and an infinite `L`-structure
`M`, then `M` has an elementary extension of cardinality `κ`.
## Implementation Details
- Satisfiability of an `L.Theory` `T` is defined in the minimal universe containing all the symbols
of `L`. By Löwenheim-Skolem, this is equivalent to satisfiability in any universe.
-/
universe u v w w'
open Cardinal CategoryTheory
open Cardinal FirstOrder
namespace FirstOrder
namespace Language
variable {L : Language.{u, v}} {T : L.Theory} {α : Type w} {n : ℕ}
namespace Theory
variable (T)
/-- A theory is satisfiable if a structure models it. -/
def IsSatisfiable : Prop :=
Nonempty (ModelType.{u, v, max u v} T)
/-- A theory is finitely satisfiable if all of its finite subtheories are satisfiable. -/
def IsFinitelySatisfiable : Prop :=
∀ T0 : Finset L.Sentence, (T0 : L.Theory) ⊆ T → IsSatisfiable (T0 : L.Theory)
variable {T} {T' : L.Theory}
theorem Model.isSatisfiable (M : Type w) [Nonempty M] [L.Structure M] [M ⊨ T] :
T.IsSatisfiable :=
⟨((⊥ : Substructure _ (ModelType.of T M)).elementarySkolem₁Reduct.toModel T).shrink⟩
theorem IsSatisfiable.mono (h : T'.IsSatisfiable) (hs : T ⊆ T') : T.IsSatisfiable :=
⟨(Theory.Model.mono (ModelType.is_model h.some) hs).bundled⟩
theorem isSatisfiable_empty (L : Language.{u, v}) : IsSatisfiable (∅ : L.Theory) :=
⟨default⟩
theorem isSatisfiable_of_isSatisfiable_onTheory {L' : Language.{w, w'}} (φ : L →ᴸ L')
(h : (φ.onTheory T).IsSatisfiable) : T.IsSatisfiable :=
Model.isSatisfiable (h.some.reduct φ)
theorem isSatisfiable_onTheory_iff {L' : Language.{w, w'}} {φ : L →ᴸ L'} (h : φ.Injective) :
(φ.onTheory T).IsSatisfiable ↔ T.IsSatisfiable := by
classical
refine ⟨isSatisfiable_of_isSatisfiable_onTheory φ, fun h' => ?_⟩
haveI : Inhabited h'.some := Classical.inhabited_of_nonempty'
exact Model.isSatisfiable (h'.some.defaultExpansion h)
theorem IsSatisfiable.isFinitelySatisfiable (h : T.IsSatisfiable) : T.IsFinitelySatisfiable :=
fun _ => h.mono
/-- The **Compactness Theorem of first-order logic**: A theory is satisfiable if and only if it is
finitely satisfiable. -/
theorem isSatisfiable_iff_isFinitelySatisfiable {T : L.Theory} :
T.IsSatisfiable ↔ T.IsFinitelySatisfiable :=
⟨Theory.IsSatisfiable.isFinitelySatisfiable, fun h => by
classical
set M : Finset T → Type max u v := fun T0 : Finset T =>
(h (T0.map (Function.Embedding.subtype fun x => x ∈ T)) T0.map_subtype_subset).some.Carrier
let M' := Filter.Product (Ultrafilter.of (Filter.atTop : Filter (Finset T))) M
have h' : M' ⊨ T := by
refine ⟨fun φ hφ => ?_⟩
rw [Ultraproduct.sentence_realize]
refine
Filter.Eventually.filter_mono (Ultrafilter.of_le _)
(Filter.eventually_atTop.2
⟨{⟨φ, hφ⟩}, fun s h' =>
Theory.realize_sentence_of_mem (s.map (Function.Embedding.subtype fun x => x ∈ T))
?_⟩)
simp only [Finset.coe_map, Function.Embedding.coe_subtype, Set.mem_image, Finset.mem_coe,
Subtype.exists, Subtype.coe_mk, exists_and_right, exists_eq_right]
exact ⟨hφ, h' (Finset.mem_singleton_self _)⟩
exact ⟨ModelType.of T M'⟩⟩
theorem isSatisfiable_directed_union_iff {ι : Type*} [Nonempty ι] {T : ι → L.Theory}
(h : Directed (· ⊆ ·) T) : Theory.IsSatisfiable (⋃ i, T i) ↔ ∀ i, (T i).IsSatisfiable := by
refine ⟨fun h' i => h'.mono (Set.subset_iUnion _ _), fun h' => ?_⟩
rw [isSatisfiable_iff_isFinitelySatisfiable, IsFinitelySatisfiable]
intro T0 hT0
obtain ⟨i, hi⟩ := h.exists_mem_subset_of_finset_subset_biUnion hT0
exact (h' i).mono hi
theorem isSatisfiable_union_distinctConstantsTheory_of_card_le (T : L.Theory) (s : Set α)
(M : Type w') [Nonempty M] [L.Structure M] [M ⊨ T]
(h : Cardinal.lift.{w'} #s ≤ Cardinal.lift.{w} #M) :
((L.lhomWithConstants α).onTheory T ∪ L.distinctConstantsTheory s).IsSatisfiable := by
haveI : Inhabited M := Classical.inhabited_of_nonempty inferInstance
rw [Cardinal.lift_mk_le'] at h
letI : (constantsOn α).Structure M := constantsOn.structure (Function.extend (↑) h.some default)
have : M ⊨ (L.lhomWithConstants α).onTheory T ∪ L.distinctConstantsTheory s := by
refine ((LHom.onTheory_model _ _).2 inferInstance).union ?_
rw [model_distinctConstantsTheory]
refine fun a as b bs ab => ?_
rw [← Subtype.coe_mk a as, ← Subtype.coe_mk b bs, ← Subtype.ext_iff]
exact
h.some.injective
((Subtype.coe_injective.extend_apply h.some default ⟨a, as⟩).symm.trans
(ab.trans (Subtype.coe_injective.extend_apply h.some default ⟨b, bs⟩)))
exact Model.isSatisfiable M
theorem isSatisfiable_union_distinctConstantsTheory_of_infinite (T : L.Theory) (s : Set α)
(M : Type w') [L.Structure M] [M ⊨ T] [Infinite M] :
((L.lhomWithConstants α).onTheory T ∪ L.distinctConstantsTheory s).IsSatisfiable := by
classical
rw [distinctConstantsTheory_eq_iUnion, Set.union_iUnion, isSatisfiable_directed_union_iff]
· exact fun t =>
isSatisfiable_union_distinctConstantsTheory_of_card_le T _ M
((lift_le_aleph0.2 (finset_card_lt_aleph0 _).le).trans
(aleph0_le_lift.2 (aleph0_le_mk M)))
· apply Monotone.directed_le
refine monotone_const.union (monotone_distinctConstantsTheory.comp ?_)
simp only [Finset.coe_map, Function.Embedding.coe_subtype]
exact Monotone.comp (g := Set.image ((↑) : s → α)) (f := ((↑) : Finset s → Set s))
Set.monotone_image fun _ _ => Finset.coe_subset.2
/-- Any theory with an infinite model has arbitrarily large models. -/
theorem exists_large_model_of_infinite_model (T : L.Theory) (κ : Cardinal.{w}) (M : Type w')
[L.Structure M] [M ⊨ T] [Infinite M] :
∃ N : ModelType.{_, _, max u v w} T, Cardinal.lift.{max u v w} κ ≤ #N := by
obtain ⟨N⟩ :=
isSatisfiable_union_distinctConstantsTheory_of_infinite T (Set.univ : Set κ.out) M
refine ⟨(N.is_model.mono Set.subset_union_left).bundled.reduct _, ?_⟩
haveI : N ⊨ distinctConstantsTheory _ _ := N.is_model.mono Set.subset_union_right
rw [ModelType.reduct_Carrier, coe_of]
refine _root_.trans (lift_le.2 (le_of_eq (Cardinal.mk_out κ).symm)) ?_
rw [← mk_univ]
refine
(card_le_of_model_distinctConstantsTheory L Set.univ N).trans (lift_le.{max u v w}.1 ?_)
rw [lift_lift]
theorem isSatisfiable_iUnion_iff_isSatisfiable_iUnion_finset {ι : Type*} (T : ι → L.Theory) :
IsSatisfiable (⋃ i, T i) ↔ ∀ s : Finset ι, IsSatisfiable (⋃ i ∈ s, T i) := by
classical
refine
⟨fun h s => h.mono (Set.iUnion_mono fun _ => Set.iUnion_subset_iff.2 fun _ => refl _),
fun h => ?_⟩
rw [isSatisfiable_iff_isFinitelySatisfiable]
intro s hs
rw [Set.iUnion_eq_iUnion_finset] at hs
obtain ⟨t, ht⟩ := Directed.exists_mem_subset_of_finset_subset_biUnion (by
exact Monotone.directed_le fun t1 t2 (h : ∀ ⦃x⦄, x ∈ t1 → x ∈ t2) =>
Set.iUnion_mono fun _ => Set.iUnion_mono' fun h1 => ⟨h h1, refl _⟩) hs
exact (h t).mono ht
end Theory
variable (L)
/-- A version of The Downward Löwenheim–Skolem theorem where the structure `N` elementarily embeds
into `M`, but is not by type a substructure of `M`, and thus can be chosen to belong to the universe
of the cardinal `κ`.
-/
theorem exists_elementaryEmbedding_card_eq_of_le (M : Type w') [L.Structure M] [Nonempty M]
(κ : Cardinal.{w}) (h1 : ℵ₀ ≤ κ) (h2 : lift.{w} L.card ≤ Cardinal.lift.{max u v} κ)
(h3 : lift.{w'} κ ≤ Cardinal.lift.{w} #M) :
∃ N : Bundled L.Structure, Nonempty (N ↪ₑ[L] M) ∧ #N = κ := by
obtain ⟨S, _, hS⟩ := exists_elementarySubstructure_card_eq L ∅ κ h1 (by simp) h2 h3
have : Small.{w} S := by
rw [← lift_inj.{_, w + 1}, lift_lift, lift_lift] at hS
exact small_iff_lift_mk_lt_univ.2 (lt_of_eq_of_lt hS κ.lift_lt_univ')
refine
⟨(equivShrink S).bundledInduced L,
⟨S.subtype.comp (Equiv.bundledInducedEquiv L _).symm.toElementaryEmbedding⟩,
lift_inj.1 (_root_.trans ?_ hS)⟩
simp only [Equiv.bundledInduced_α, lift_mk_shrink']
section
/-- The **Upward Löwenheim–Skolem Theorem**: If `κ` is a cardinal greater than the cardinalities of
`L` and an infinite `L`-structure `M`, then `M` has an elementary extension of cardinality `κ`. -/
theorem exists_elementaryEmbedding_card_eq_of_ge (M : Type w') [L.Structure M] [iM : Infinite M]
(κ : Cardinal.{w}) (h1 : Cardinal.lift.{w} L.card ≤ Cardinal.lift.{max u v} κ)
(h2 : Cardinal.lift.{w} #M ≤ Cardinal.lift.{w'} κ) :
∃ N : Bundled L.Structure, Nonempty (M ↪ₑ[L] N) ∧ #N = κ := by
obtain ⟨N0, hN0⟩ := (L.elementaryDiagram M).exists_large_model_of_infinite_model κ M
rw [← lift_le.{max u v}, lift_lift, lift_lift] at h2
obtain ⟨N, ⟨NN0⟩, hN⟩ :=
exists_elementaryEmbedding_card_eq_of_le (L[[M]]) N0 κ
(aleph0_le_lift.1 ((aleph0_le_lift.2 (aleph0_le_mk M)).trans h2))
(by
simp only [card_withConstants, lift_add, lift_lift]
rw [add_comm, add_eq_max (aleph0_le_lift.2 (infinite_iff.1 iM)), max_le_iff]
rw [← lift_le.{w'}, lift_lift, lift_lift] at h1
exact ⟨h2, h1⟩)
(hN0.trans (by rw [← lift_umax, lift_id]))
letI := (lhomWithConstants L M).reduct N
haveI h : N ⊨ L.elementaryDiagram M :=
(NN0.theory_model_iff (L.elementaryDiagram M)).2 inferInstance
refine ⟨Bundled.of N, ⟨?_⟩, hN⟩
apply ElementaryEmbedding.ofModelsElementaryDiagram L M N
end
/-- The Löwenheim–Skolem Theorem: If `κ` is a cardinal greater than the cardinalities of `L`
and an infinite `L`-structure `M`, then there is an elementary embedding in the appropriate
direction between then `M` and a structure of cardinality `κ`. -/
theorem exists_elementaryEmbedding_card_eq (M : Type w') [L.Structure M] [iM : Infinite M]
(κ : Cardinal.{w}) (h1 : ℵ₀ ≤ κ) (h2 : lift.{w} L.card ≤ Cardinal.lift.{max u v} κ) :
∃ N : Bundled L.Structure, (Nonempty (N ↪ₑ[L] M) ∨ Nonempty (M ↪ₑ[L] N)) ∧ #N = κ := by
cases le_or_gt (lift.{w'} κ) (Cardinal.lift.{w} #M) with
| inl h =>
obtain ⟨N, hN1, hN2⟩ := exists_elementaryEmbedding_card_eq_of_le L M κ h1 h2 h
exact ⟨N, Or.inl hN1, hN2⟩
| inr h =>
obtain ⟨N, hN1, hN2⟩ := exists_elementaryEmbedding_card_eq_of_ge L M κ h2 (le_of_lt h)
exact ⟨N, Or.inr hN1, hN2⟩
/-- A consequence of the Löwenheim–Skolem Theorem: If `κ` is a cardinal greater than the
cardinalities of `L` and an infinite `L`-structure `M`, then there is a structure of cardinality `κ`
elementarily equivalent to `M`. -/
theorem exists_elementarilyEquivalent_card_eq (M : Type w') [L.Structure M] [Infinite M]
(κ : Cardinal.{w}) (h1 : ℵ₀ ≤ κ) (h2 : lift.{w} L.card ≤ Cardinal.lift.{max u v} κ) :
∃ N : CategoryTheory.Bundled L.Structure, (M ≅[L] N) ∧ #N = κ := by
obtain ⟨N, NM | MN, hNκ⟩ := exists_elementaryEmbedding_card_eq L M κ h1 h2
· exact ⟨N, NM.some.elementarilyEquivalent.symm, hNκ⟩
· exact ⟨N, MN.some.elementarilyEquivalent, hNκ⟩
variable {L}
namespace Theory
theorem exists_model_card_eq (h : ∃ M : ModelType.{u, v, max u v} T, Infinite M) (κ : Cardinal.{w})
(h1 : ℵ₀ ≤ κ) (h2 : Cardinal.lift.{w} L.card ≤ Cardinal.lift.{max u v} κ) :
∃ N : ModelType.{u, v, w} T, #N = κ := by
cases h with
| intro M MI =>
haveI := MI
obtain ⟨N, hN, rfl⟩ := exists_elementarilyEquivalent_card_eq L M κ h1 h2
haveI : Nonempty N := hN.nonempty
exact ⟨hN.theory_model.bundled, rfl⟩
variable (T)
/-- A theory models a (bounded) formula when any of its nonempty models realizes that formula on all
inputs. -/
def ModelsBoundedFormula (φ : L.BoundedFormula α n) : Prop :=
∀ (M : ModelType.{u, v, max u v w} T) (v : α → M) (xs : Fin n → M), φ.Realize v xs
@[inherit_doc FirstOrder.Language.Theory.ModelsBoundedFormula]
infixl:51 " ⊨ᵇ " => ModelsBoundedFormula -- input using \|= or \vDash, but not using \models
variable {T}
theorem models_formula_iff {φ : L.Formula α} :
T ⊨ᵇ φ ↔ ∀ (M : ModelType.{u, v, max u v w} T) (v : α → M), φ.Realize v :=
forall_congr' fun _ => forall_congr' fun _ => Unique.forall_iff
theorem models_sentence_iff {φ : L.Sentence} : T ⊨ᵇ φ ↔ ∀ M : ModelType.{u, v, max u v} T, M ⊨ φ :=
models_formula_iff.trans (forall_congr' fun _ => Unique.forall_iff)
theorem models_sentence_of_mem {φ : L.Sentence} (h : φ ∈ T) : T ⊨ᵇ φ :=
models_sentence_iff.2 fun _ => realize_sentence_of_mem T h
theorem models_iff_not_satisfiable (φ : L.Sentence) : T ⊨ᵇ φ ↔ ¬IsSatisfiable (T ∪ {φ.not}) := by
rw [models_sentence_iff, IsSatisfiable]
refine
⟨fun h1 h2 =>
(Sentence.realize_not _).1
(realize_sentence_of_mem (T ∪ {Formula.not φ})
(Set.subset_union_right (Set.mem_singleton _)))
(h1 (h2.some.subtheoryModel Set.subset_union_left)),
fun h M => ?_⟩
contrapose! h
rw [← Sentence.realize_not] at h
refine
⟨{ Carrier := M
is_model := ⟨fun ψ hψ => hψ.elim (realize_sentence_of_mem _) fun h' => ?_⟩ }⟩
rw [Set.mem_singleton_iff.1 h']
exact h
theorem ModelsBoundedFormula.realize_sentence {φ : L.Sentence} (h : T ⊨ᵇ φ) (M : Type*)
[L.Structure M] [M ⊨ T] [Nonempty M] : M ⊨ φ := by
rw [models_iff_not_satisfiable] at h
contrapose! h
have : M ⊨ T ∪ {Formula.not φ} := by
simp only [Set.union_singleton, model_iff, Set.mem_insert_iff, forall_eq_or_imp,
Sentence.realize_not]
rw [← model_iff]
exact ⟨h, inferInstance⟩
exact Model.isSatisfiable M
theorem models_formula_iff_onTheory_models_equivSentence {φ : L.Formula α} :
T ⊨ᵇ φ ↔ (L.lhomWithConstants α).onTheory T ⊨ᵇ Formula.equivSentence φ := by
refine ⟨fun h => models_sentence_iff.2 (fun M => ?_),
fun h => models_formula_iff.2 (fun M v => ?_)⟩
· letI := (L.lhomWithConstants α).reduct M
have : (L.lhomWithConstants α).IsExpansionOn M := LHom.isExpansionOn_reduct _ _
-- why doesn't that instance just work?
rw [Formula.realize_equivSentence]
have : M ⊨ T := (LHom.onTheory_model _ _).1 M.is_model -- why isn't M.is_model inferInstance?
let M' := Theory.ModelType.of T M
exact h M' (fun a => (L.con a : M)) _
· letI : (constantsOn α).Structure M := constantsOn.structure v
have : M ⊨ (L.lhomWithConstants α).onTheory T := (LHom.onTheory_model _ _).2 inferInstance
exact (Formula.realize_equivSentence _ _).1 (h.realize_sentence M)
theorem ModelsBoundedFormula.realize_formula {φ : L.Formula α} (h : T ⊨ᵇ φ) (M : Type*)
[L.Structure M] [M ⊨ T] [Nonempty M] {v : α → M} : φ.Realize v := by
rw [models_formula_iff_onTheory_models_equivSentence] at h
letI : (constantsOn α).Structure M := constantsOn.structure v
have : M ⊨ (L.lhomWithConstants α).onTheory T := (LHom.onTheory_model _ _).2 inferInstance
exact (Formula.realize_equivSentence _ _).1 (h.realize_sentence M)
theorem models_toFormula_iff {φ : L.BoundedFormula α n} : T ⊨ᵇ φ.toFormula ↔ T ⊨ᵇ φ := by
refine ⟨fun h M v xs => ?_, ?_⟩
· have h' : φ.toFormula.Realize (Sum.elim v xs) := h.realize_formula M
simp only [BoundedFormula.realize_toFormula, Sum.elim_comp_inl, Sum.elim_comp_inr] at h'
exact h'
· simp only [models_formula_iff, BoundedFormula.realize_toFormula]
exact fun h M v => h M _ _
theorem ModelsBoundedFormula.realize_boundedFormula
{φ : L.BoundedFormula α n} (h : T ⊨ᵇ φ) (M : Type*)
[L.Structure M] [M ⊨ T] [Nonempty M] {v : α → M} {xs : Fin n → M} : φ.Realize v xs := by
have h' : φ.toFormula.Realize (Sum.elim v xs) := (models_toFormula_iff.2 h).realize_formula M
simp only [BoundedFormula.realize_toFormula, Sum.elim_comp_inl, Sum.elim_comp_inr] at h'
exact h'
theorem models_of_models_theory {T' : L.Theory}
(h : ∀ φ : L.Sentence, φ ∈ T' → T ⊨ᵇ φ)
{φ : L.Formula α} (hφ : T' ⊨ᵇ φ) : T ⊨ᵇ φ := fun M => by
have hM : M ⊨ T' := T'.model_iff.2 (fun ψ hψ => (h ψ hψ).realize_sentence M)
let M' : ModelType T' := ⟨M⟩
exact hφ M'
/-- An alternative statement of the Compactness Theorem. A formula `φ` is modeled by a
theory iff there is a finite subset `T0` of the theory such that `φ` is modeled by `T0` -/
theorem models_iff_finset_models {φ : L.Sentence} :
T ⊨ᵇ φ ↔ ∃ T0 : Finset L.Sentence, (T0 : L.Theory) ⊆ T ∧ (T0 : L.Theory) ⊨ᵇ φ := by
simp only [models_iff_not_satisfiable]
rw [← not_iff_not, not_not, isSatisfiable_iff_isFinitelySatisfiable, IsFinitelySatisfiable]
push_neg
letI := Classical.decEq (Sentence L)
constructor
· intro h T0 hT0
simpa using h (T0 ∪ {Formula.not φ})
(by
simp only [Finset.coe_union, Finset.coe_singleton]
exact Set.union_subset_union hT0 (Set.Subset.refl _))
· intro h T0 hT0
exact IsSatisfiable.mono (h (T0.erase (Formula.not φ))
(by simpa using hT0)) (by simp)
/-- A theory is complete when it is satisfiable and models each sentence or its negation. -/
def IsComplete (T : L.Theory) : Prop :=
T.IsSatisfiable ∧ ∀ φ : L.Sentence, T ⊨ᵇ φ ∨ T ⊨ᵇ φ.not
namespace IsComplete
theorem models_not_iff (h : T.IsComplete) (φ : L.Sentence) : T ⊨ᵇ φ.not ↔ ¬T ⊨ᵇ φ := by
rcases h.2 φ with hφ | hφn
· simp only [hφ, not_true, iff_false]
rw [models_sentence_iff, not_forall]
refine ⟨h.1.some, ?_⟩
simp only [Sentence.realize_not, Classical.not_not]
exact models_sentence_iff.1 hφ _
· simp only [hφn, true_iff]
intro hφ
rw [models_sentence_iff] at *
exact hφn h.1.some (hφ _)
theorem realize_sentence_iff (h : T.IsComplete) (φ : L.Sentence) (M : Type*) [L.Structure M]
[M ⊨ T] [Nonempty M] : M ⊨ φ ↔ T ⊨ᵇ φ := by
rcases h.2 φ with hφ | hφn
· exact iff_of_true (hφ.realize_sentence M) hφ
· exact
iff_of_false ((Sentence.realize_not M).1 (hφn.realize_sentence M))
((h.models_not_iff φ).1 hφn)
end IsComplete
/-- A theory is maximal when it is satisfiable and contains each sentence or its negation.
Maximal theories are complete. -/
def IsMaximal (T : L.Theory) : Prop :=
T.IsSatisfiable ∧ ∀ φ : L.Sentence, φ ∈ T ∨ φ.not ∈ T
theorem IsMaximal.isComplete (h : T.IsMaximal) : T.IsComplete :=
h.imp_right (forall_imp fun _ => Or.imp models_sentence_of_mem models_sentence_of_mem)
theorem IsMaximal.mem_or_not_mem (h : T.IsMaximal) (φ : L.Sentence) : φ ∈ T ∨ φ.not ∈ T :=
h.2 φ
| Mathlib/ModelTheory/Satisfiability.lean | 427 | 430 | theorem IsMaximal.mem_of_models (h : T.IsMaximal) {φ : L.Sentence} (hφ : T ⊨ᵇ φ) : φ ∈ T := by | refine (h.mem_or_not_mem φ).resolve_right fun con => ?_
rw [models_iff_not_satisfiable, Set.union_singleton, Set.insert_eq_of_mem con] at hφ
exact hφ h.1 |
/-
Copyright (c) 2023 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Dynamics.Ergodic.Ergodic
import Mathlib.MeasureTheory.Function.AEEqFun
/-!
# Functions invariant under (quasi)ergodic map
In this file we prove that an a.e. strongly measurable function `g : α → X`
that is a.e. invariant under a (quasi)ergodic map is a.e. equal to a constant.
We prove several versions of this statement with slightly different measurability assumptions.
We also formulate a version for `MeasureTheory.AEEqFun` functions
with all a.e. equalities replaced with equalities in the quotient space.
-/
open Function Set Filter MeasureTheory Topology TopologicalSpace
variable {α X : Type*} [MeasurableSpace α] {μ : MeasureTheory.Measure α}
/-- Let `f : α → α` be a (quasi)ergodic map. Let `g : α → X` is a null-measurable function
from `α` to a nonempty space with a countable family of measurable sets
separating points of a set `s` such that `f x ∈ s` for a.e. `x`.
If `g` that is a.e.-invariant under `f`, then `g` is a.e. constant. -/
| Mathlib/Dynamics/Ergodic/Function.lean | 27 | 35 | theorem QuasiErgodic.ae_eq_const_of_ae_eq_comp_of_ae_range₀ [Nonempty X] [MeasurableSpace X]
{s : Set X} [MeasurableSpace.CountablySeparated s] {f : α → α} {g : α → X}
(h : QuasiErgodic f μ) (hs : ∀ᵐ x ∂μ, g x ∈ s) (hgm : NullMeasurable g μ)
(hg_eq : g ∘ f =ᵐ[μ] g) :
∃ c, g =ᵐ[μ] const α c := by | refine exists_eventuallyEq_const_of_eventually_mem_of_forall_separating MeasurableSet hs ?_
refine fun U hU ↦ h.ae_mem_or_ae_nmem₀ (s := g ⁻¹' U) (hgm hU) ?_b
refine (hg_eq.mono fun x hx ↦ ?_).set_eq
rw [← preimage_comp, mem_preimage, mem_preimage, hx] |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne
-/
import Mathlib.Analysis.SpecialFunctions.Exp
import Mathlib.Data.Nat.Factorization.Defs
import Mathlib.Analysis.NormedSpace.Real
import Mathlib.Data.Rat.Cast.CharZero
/-!
# Real logarithm
In this file we define `Real.log` to be the logarithm of a real number. As usual, we extend it from
its domain `(0, +∞)` to a globally defined function. We choose to do it so that `log 0 = 0` and
`log (-x) = log x`.
We prove some basic properties of this function and show that it is continuous.
## Tags
logarithm, continuity
-/
open Set Filter Function
open Topology
noncomputable section
namespace Real
variable {x y : ℝ}
/-- The real logarithm function, equal to the inverse of the exponential for `x > 0`,
to `log |x|` for `x < 0`, and to `0` for `0`. We use this unconventional extension to
`(-∞, 0]` as it gives the formula `log (x * y) = log x + log y` for all nonzero `x` and `y`, and
the derivative of `log` is `1/x` away from `0`. -/
@[pp_nodot]
noncomputable def log (x : ℝ) : ℝ :=
if hx : x = 0 then 0 else expOrderIso.symm ⟨|x|, abs_pos.2 hx⟩
theorem log_of_ne_zero (hx : x ≠ 0) : log x = expOrderIso.symm ⟨|x|, abs_pos.2 hx⟩ :=
dif_neg hx
theorem log_of_pos (hx : 0 < x) : log x = expOrderIso.symm ⟨x, hx⟩ := by
rw [log_of_ne_zero hx.ne']
congr
exact abs_of_pos hx
theorem exp_log_eq_abs (hx : x ≠ 0) : exp (log x) = |x| := by
rw [log_of_ne_zero hx, ← coe_expOrderIso_apply, OrderIso.apply_symm_apply, Subtype.coe_mk]
theorem exp_log (hx : 0 < x) : exp (log x) = x := by
rw [exp_log_eq_abs hx.ne']
exact abs_of_pos hx
theorem exp_log_of_neg (hx : x < 0) : exp (log x) = -x := by
rw [exp_log_eq_abs (ne_of_lt hx)]
exact abs_of_neg hx
theorem le_exp_log (x : ℝ) : x ≤ exp (log x) := by
by_cases h_zero : x = 0
· rw [h_zero, log, dif_pos rfl, exp_zero]
exact zero_le_one
· rw [exp_log_eq_abs h_zero]
exact le_abs_self _
@[simp]
theorem log_exp (x : ℝ) : log (exp x) = x :=
exp_injective <| exp_log (exp_pos x)
theorem exp_one_mul_le_exp {x : ℝ} : exp 1 * x ≤ exp x := by
by_cases hx0 : x ≤ 0
· apply le_trans (mul_nonpos_of_nonneg_of_nonpos (exp_pos 1).le hx0) (exp_nonneg x)
· have h := add_one_le_exp (log x)
rwa [← exp_le_exp, exp_add, exp_log (lt_of_not_le hx0), mul_comm] at h
theorem two_mul_le_exp {x : ℝ} : 2 * x ≤ exp x := by
by_cases hx0 : x < 0
· exact le_trans (mul_nonpos_of_nonneg_of_nonpos (by simp only [Nat.ofNat_nonneg]) hx0.le)
(exp_nonneg x)
· apply le_trans (mul_le_mul_of_nonneg_right _ (le_of_not_lt hx0)) exp_one_mul_le_exp
have := Real.add_one_le_exp 1
rwa [one_add_one_eq_two] at this
theorem surjOn_log : SurjOn log (Ioi 0) univ := fun x _ => ⟨exp x, exp_pos x, log_exp x⟩
theorem log_surjective : Surjective log := fun x => ⟨exp x, log_exp x⟩
@[simp]
theorem range_log : range log = univ :=
log_surjective.range_eq
@[simp]
theorem log_zero : log 0 = 0 :=
dif_pos rfl
@[simp]
theorem log_one : log 1 = 0 :=
exp_injective <| by rw [exp_log zero_lt_one, exp_zero]
/-- This holds true for all `x : ℝ` because of the junk values `0 / 0 = 0` and `log 0 = 0`. -/
@[simp] lemma log_div_self (x : ℝ) : log (x / x) = 0 := by
obtain rfl | hx := eq_or_ne x 0 <;> simp [*]
@[simp]
theorem log_abs (x : ℝ) : log |x| = log x := by
by_cases h : x = 0
· simp [h]
· rw [← exp_eq_exp, exp_log_eq_abs h, exp_log_eq_abs (abs_pos.2 h).ne', abs_abs]
@[simp]
theorem log_neg_eq_log (x : ℝ) : log (-x) = log x := by rw [← log_abs x, ← log_abs (-x), abs_neg]
theorem sinh_log {x : ℝ} (hx : 0 < x) : sinh (log x) = (x - x⁻¹) / 2 := by
rw [sinh_eq, exp_neg, exp_log hx]
theorem cosh_log {x : ℝ} (hx : 0 < x) : cosh (log x) = (x + x⁻¹) / 2 := by
rw [cosh_eq, exp_neg, exp_log hx]
theorem surjOn_log' : SurjOn log (Iio 0) univ := fun x _ =>
⟨-exp x, neg_lt_zero.2 <| exp_pos x, by rw [log_neg_eq_log, log_exp]⟩
theorem log_mul (hx : x ≠ 0) (hy : y ≠ 0) : log (x * y) = log x + log y :=
exp_injective <| by
rw [exp_log_eq_abs (mul_ne_zero hx hy), exp_add, exp_log_eq_abs hx, exp_log_eq_abs hy, abs_mul]
theorem log_div (hx : x ≠ 0) (hy : y ≠ 0) : log (x / y) = log x - log y :=
exp_injective <| by
rw [exp_log_eq_abs (div_ne_zero hx hy), exp_sub, exp_log_eq_abs hx, exp_log_eq_abs hy, abs_div]
@[simp]
theorem log_inv (x : ℝ) : log x⁻¹ = -log x := by
by_cases hx : x = 0; · simp [hx]
rw [← exp_eq_exp, exp_log_eq_abs (inv_ne_zero hx), exp_neg, exp_log_eq_abs hx, abs_inv]
theorem log_le_log_iff (h : 0 < x) (h₁ : 0 < y) : log x ≤ log y ↔ x ≤ y := by
rw [← exp_le_exp, exp_log h, exp_log h₁]
@[gcongr, bound]
lemma log_le_log (hx : 0 < x) (hxy : x ≤ y) : log x ≤ log y :=
(log_le_log_iff hx (hx.trans_le hxy)).2 hxy
@[gcongr, bound]
theorem log_lt_log (hx : 0 < x) (h : x < y) : log x < log y := by
rwa [← exp_lt_exp, exp_log hx, exp_log (lt_trans hx h)]
theorem log_lt_log_iff (hx : 0 < x) (hy : 0 < y) : log x < log y ↔ x < y := by
rw [← exp_lt_exp, exp_log hx, exp_log hy]
theorem log_le_iff_le_exp (hx : 0 < x) : log x ≤ y ↔ x ≤ exp y := by rw [← exp_le_exp, exp_log hx]
theorem log_lt_iff_lt_exp (hx : 0 < x) : log x < y ↔ x < exp y := by rw [← exp_lt_exp, exp_log hx]
theorem le_log_iff_exp_le (hy : 0 < y) : x ≤ log y ↔ exp x ≤ y := by rw [← exp_le_exp, exp_log hy]
theorem lt_log_iff_exp_lt (hy : 0 < y) : x < log y ↔ exp x < y := by rw [← exp_lt_exp, exp_log hy]
theorem log_pos_iff (hx : 0 ≤ x) : 0 < log x ↔ 1 < x := by
rcases hx.eq_or_lt with (rfl | hx)
· simp [le_refl, zero_le_one]
rw [← log_one]
exact log_lt_log_iff zero_lt_one hx
@[bound]
theorem log_pos (hx : 1 < x) : 0 < log x :=
(log_pos_iff (lt_trans zero_lt_one hx).le).2 hx
theorem log_pos_of_lt_neg_one (hx : x < -1) : 0 < log x := by
rw [← neg_neg x, log_neg_eq_log]
have : 1 < -x := by linarith
exact log_pos this
theorem log_neg_iff (h : 0 < x) : log x < 0 ↔ x < 1 := by
rw [← log_one]
exact log_lt_log_iff h zero_lt_one
@[bound]
theorem log_neg (h0 : 0 < x) (h1 : x < 1) : log x < 0 :=
(log_neg_iff h0).2 h1
theorem log_neg_of_lt_zero (h0 : x < 0) (h1 : -1 < x) : log x < 0 := by
rw [← neg_neg x, log_neg_eq_log]
have h0' : 0 < -x := by linarith
have h1' : -x < 1 := by linarith
exact log_neg h0' h1'
theorem log_nonneg_iff (hx : 0 < x) : 0 ≤ log x ↔ 1 ≤ x := by rw [← not_lt, log_neg_iff hx, not_lt]
@[bound]
theorem log_nonneg (hx : 1 ≤ x) : 0 ≤ log x :=
(log_nonneg_iff (zero_lt_one.trans_le hx)).2 hx
theorem log_nonpos_iff (hx : 0 ≤ x) : log x ≤ 0 ↔ x ≤ 1 := by
rcases hx.eq_or_lt with (rfl | hx)
· simp [le_refl, zero_le_one]
rw [← not_lt, log_pos_iff hx.le, not_lt]
@[deprecated (since := "2025-01-16")]
alias log_nonpos_iff' := log_nonpos_iff
@[bound]
theorem log_nonpos (hx : 0 ≤ x) (h'x : x ≤ 1) : log x ≤ 0 :=
(log_nonpos_iff hx).2 h'x
| Mathlib/Analysis/SpecialFunctions/Log/Basic.lean | 207 | 207 | theorem log_natCast_nonneg (n : ℕ) : 0 ≤ log n := by | |
/-
Copyright (c) 2022 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Algebra.Order.Group.Multiset
/-!
# Disjoint sum of multisets
This file defines the disjoint sum of two multisets as `Multiset (α ⊕ β)`. Beware not to confuse
with the `Multiset.sum` operation which computes the additive sum.
## Main declarations
* `Multiset.disjSum`: `s.disjSum t` is the disjoint sum of `s` and `t`.
-/
open Sum
namespace Multiset
variable {α β γ : Type*} (s : Multiset α) (t : Multiset β)
/-- Disjoint sum of multisets. -/
def disjSum : Multiset (α ⊕ β) :=
s.map inl + t.map inr
@[simp]
theorem zero_disjSum : (0 : Multiset α).disjSum t = t.map inr :=
Multiset.zero_add _
@[simp]
theorem disjSum_zero : s.disjSum (0 : Multiset β) = s.map inl :=
Multiset.add_zero _
@[simp]
theorem card_disjSum : Multiset.card (s.disjSum t) = Multiset.card s + Multiset.card t := by
rw [disjSum, card_add, card_map, card_map]
variable {s t} {s₁ s₂ : Multiset α} {t₁ t₂ : Multiset β} {a : α} {b : β} {x : α ⊕ β}
theorem mem_disjSum : x ∈ s.disjSum t ↔ (∃ a, a ∈ s ∧ inl a = x) ∨ ∃ b, b ∈ t ∧ inr b = x := by
simp_rw [disjSum, mem_add, mem_map]
@[simp]
theorem inl_mem_disjSum : inl a ∈ s.disjSum t ↔ a ∈ s := by
rw [mem_disjSum, or_iff_left]
· simp only [inl.injEq, exists_eq_right]
rintro ⟨b, _, hb⟩
exact inr_ne_inl hb
@[simp]
| Mathlib/Data/Multiset/Sum.lean | 55 | 60 | theorem inr_mem_disjSum : inr b ∈ s.disjSum t ↔ b ∈ t := by | rw [mem_disjSum, or_iff_right]
· simp only [inr.injEq, exists_eq_right]
rintro ⟨a, _, ha⟩
exact inl_ne_inr ha |
/-
Copyright (c) 2021 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying, Eric Wieser
-/
import Mathlib.Data.Real.Basic
import Mathlib.Tactic.NormNum.Inv
/-!
# Real sign function
This file introduces and contains some results about `Real.sign` which maps negative
real numbers to -1, positive real numbers to 1, and 0 to 0.
## Main definitions
* `Real.sign r` is $\begin{cases} -1 & \text{if } r < 0, \\
~~\, 0 & \text{if } r = 0, \\
~~\, 1 & \text{if } r > 0. \end{cases}$
## Tags
sign function
-/
namespace Real
/-- The sign function that maps negative real numbers to -1, positive numbers to 1, and 0
otherwise. -/
noncomputable def sign (r : ℝ) : ℝ :=
if r < 0 then -1 else if 0 < r then 1 else 0
theorem sign_of_neg {r : ℝ} (hr : r < 0) : sign r = -1 := by rw [sign, if_pos hr]
theorem sign_of_pos {r : ℝ} (hr : 0 < r) : sign r = 1 := by rw [sign, if_pos hr, if_neg hr.not_lt]
@[simp]
theorem sign_zero : sign 0 = 0 := by rw [sign, if_neg (lt_irrefl _), if_neg (lt_irrefl _)]
@[simp]
theorem sign_one : sign 1 = 1 :=
sign_of_pos <| by norm_num
theorem sign_apply_eq (r : ℝ) : sign r = -1 ∨ sign r = 0 ∨ sign r = 1 := by
obtain hn | rfl | hp := lt_trichotomy r (0 : ℝ)
· exact Or.inl <| sign_of_neg hn
· exact Or.inr <| Or.inl <| sign_zero
· exact Or.inr <| Or.inr <| sign_of_pos hp
/-- This lemma is useful for working with `ℝˣ` -/
theorem sign_apply_eq_of_ne_zero (r : ℝ) (h : r ≠ 0) : sign r = -1 ∨ sign r = 1 :=
h.lt_or_lt.imp sign_of_neg sign_of_pos
@[simp]
theorem sign_eq_zero_iff {r : ℝ} : sign r = 0 ↔ r = 0 := by
refine ⟨fun h => ?_, fun h => h.symm ▸ sign_zero⟩
obtain hn | rfl | hp := lt_trichotomy r (0 : ℝ)
· rw [sign_of_neg hn, neg_eq_zero] at h
exact (one_ne_zero h).elim
· rfl
· rw [sign_of_pos hp] at h
exact (one_ne_zero h).elim
theorem sign_intCast (z : ℤ) : sign (z : ℝ) = ↑(Int.sign z) := by
obtain hn | rfl | hp := lt_trichotomy z (0 : ℤ)
· rw [sign_of_neg (Int.cast_lt_zero.mpr hn), Int.sign_eq_neg_one_of_neg hn, Int.cast_neg,
Int.cast_one]
· rw [Int.cast_zero, sign_zero, Int.sign_zero, Int.cast_zero]
· rw [sign_of_pos (Int.cast_pos.mpr hp), Int.sign_eq_one_of_pos hp, Int.cast_one]
theorem sign_neg {r : ℝ} : sign (-r) = -sign r := by
obtain hn | rfl | hp := lt_trichotomy r (0 : ℝ)
· rw [sign_of_neg hn, sign_of_pos (neg_pos.mpr hn), neg_neg]
· rw [sign_zero, neg_zero, sign_zero]
· rw [sign_of_pos hp, sign_of_neg (neg_lt_zero.mpr hp)]
theorem sign_mul_nonneg (r : ℝ) : 0 ≤ sign r * r := by
obtain hn | rfl | hp := lt_trichotomy r (0 : ℝ)
· rw [sign_of_neg hn]
exact mul_nonneg_of_nonpos_of_nonpos (by norm_num) hn.le
· rw [mul_zero]
· rw [sign_of_pos hp, one_mul]
exact hp.le
| Mathlib/Data/Real/Sign.lean | 86 | 90 | theorem sign_mul_pos_of_ne_zero (r : ℝ) (hr : r ≠ 0) : 0 < sign r * r := by | refine lt_of_le_of_ne (sign_mul_nonneg r) fun h => hr ?_
have hs0 := (zero_eq_mul.mp h).resolve_right hr
exact sign_eq_zero_iff.mp hs0 |
/-
Copyright (c) 2022 David Kurniadi Angdinata. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Kurniadi Angdinata
-/
import Mathlib.Algebra.Polynomial.Splits
import Mathlib.Tactic.IntervalCases
/-!
# Cubics and discriminants
This file defines cubic polynomials over a semiring and their discriminants over a splitting field.
## Main definitions
* `Cubic`: the structure representing a cubic polynomial.
* `Cubic.disc`: the discriminant of a cubic polynomial.
## Main statements
* `Cubic.disc_ne_zero_iff_roots_nodup`: the cubic discriminant is not equal to zero if and only if
the cubic has no duplicate roots.
## References
* https://en.wikipedia.org/wiki/Cubic_equation
* https://en.wikipedia.org/wiki/Discriminant
## Tags
cubic, discriminant, polynomial, root
-/
noncomputable section
/-- The structure representing a cubic polynomial. -/
@[ext]
structure Cubic (R : Type*) where
/-- The degree-3 coefficient -/
a : R
/-- The degree-2 coefficient -/
b : R
/-- The degree-1 coefficient -/
c : R
/-- The degree-0 coefficient -/
d : R
namespace Cubic
open Polynomial
variable {R S F K : Type*}
instance [Inhabited R] : Inhabited (Cubic R) :=
⟨⟨default, default, default, default⟩⟩
instance [Zero R] : Zero (Cubic R) :=
⟨⟨0, 0, 0, 0⟩⟩
section Basic
variable {P Q : Cubic R} {a b c d a' b' c' d' : R} [Semiring R]
/-- Convert a cubic polynomial to a polynomial. -/
def toPoly (P : Cubic R) : R[X] :=
C P.a * X ^ 3 + C P.b * X ^ 2 + C P.c * X + C P.d
theorem C_mul_prod_X_sub_C_eq [CommRing S] {w x y z : S} :
C w * (X - C x) * (X - C y) * (X - C z) =
toPoly ⟨w, w * -(x + y + z), w * (x * y + x * z + y * z), w * -(x * y * z)⟩ := by
simp only [toPoly, C_neg, C_add, C_mul]
ring1
| Mathlib/Algebra/CubicDiscriminant.lean | 75 | 78 | theorem prod_X_sub_C_eq [CommRing S] {x y z : S} :
(X - C x) * (X - C y) * (X - C z) =
toPoly ⟨1, -(x + y + z), x * y + x * z + y * z, -(x * y * z)⟩ := by | rw [← one_mul <| X - C x, ← C_1, C_mul_prod_X_sub_C_eq, one_mul, one_mul, one_mul] |
/-
Copyright (c) 2021 Thomas Browning. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Thomas Browning
-/
import Mathlib.Algebra.BigOperators.GroupWithZero.Finset
import Mathlib.Algebra.GroupWithZero.Subgroup
import Mathlib.Data.Finite.Card
import Mathlib.Data.Finite.Prod
import Mathlib.Data.Set.Card
import Mathlib.GroupTheory.Coset.Card
import Mathlib.GroupTheory.GroupAction.Quotient
import Mathlib.GroupTheory.QuotientGroup.Basic
/-!
# Index of a Subgroup
In this file we define the index of a subgroup, and prove several divisibility properties.
Several theorems proved in this file are known as Lagrange's theorem.
## Main definitions
- `H.index` : the index of `H : Subgroup G` as a natural number,
and returns 0 if the index is infinite.
- `H.relindex K` : the relative index of `H : Subgroup G` in `K : Subgroup G` as a natural number,
and returns 0 if the relative index is infinite.
# Main results
- `card_mul_index` : `Nat.card H * H.index = Nat.card G`
- `index_mul_card` : `H.index * Fintype.card H = Fintype.card G`
- `index_dvd_card` : `H.index ∣ Fintype.card G`
- `relindex_mul_index` : If `H ≤ K`, then `H.relindex K * K.index = H.index`
- `index_dvd_of_le` : If `H ≤ K`, then `K.index ∣ H.index`
- `relindex_mul_relindex` : `relindex` is multiplicative in towers
- `MulAction.index_stabilizer`: the index of the stabilizer is the cardinality of the orbit
-/
assert_not_exists Field
open scoped Pointwise
namespace Subgroup
open Cardinal Function
variable {G G' : Type*} [Group G] [Group G'] (H K L : Subgroup G)
/-- The index of a subgroup as a natural number. Returns `0` if the index is infinite. -/
@[to_additive "The index of an additive subgroup as a natural number.
Returns 0 if the index is infinite."]
noncomputable def index : ℕ :=
Nat.card (G ⧸ H)
/-- If `H` and `K` are subgroups of a group `G`, then `relindex H K : ℕ` is the index
of `H ∩ K` in `K`. The function returns `0` if the index is infinite. -/
@[to_additive "If `H` and `K` are subgroups of an additive group `G`, then `relindex H K : ℕ`
is the index of `H ∩ K` in `K`. The function returns `0` if the index is infinite."]
noncomputable def relindex : ℕ :=
(H.subgroupOf K).index
@[to_additive]
theorem index_comap_of_surjective {f : G' →* G} (hf : Function.Surjective f) :
(H.comap f).index = H.index := by
have key : ∀ x y : G',
QuotientGroup.leftRel (H.comap f) x y ↔ QuotientGroup.leftRel H (f x) (f y) := by
simp only [QuotientGroup.leftRel_apply]
exact fun x y => iff_of_eq (congr_arg (· ∈ H) (by rw [f.map_mul, f.map_inv]))
refine Cardinal.toNat_congr (Equiv.ofBijective (Quotient.map' f fun x y => (key x y).mp) ⟨?_, ?_⟩)
· simp_rw [← Quotient.eq''] at key
refine Quotient.ind' fun x => ?_
refine Quotient.ind' fun y => ?_
exact (key x y).mpr
· refine Quotient.ind' fun x => ?_
obtain ⟨y, hy⟩ := hf x
exact ⟨y, (Quotient.map'_mk'' f _ y).trans (congr_arg Quotient.mk'' hy)⟩
@[to_additive]
theorem index_comap (f : G' →* G) :
(H.comap f).index = H.relindex f.range :=
Eq.trans (congr_arg index (by rfl))
((H.subgroupOf f.range).index_comap_of_surjective f.rangeRestrict_surjective)
@[to_additive]
theorem relindex_comap (f : G' →* G) (K : Subgroup G') :
relindex (comap f H) K = relindex H (map f K) := by
rw [relindex, subgroupOf, comap_comap, index_comap, ← f.map_range, K.range_subtype]
variable {H K L}
@[to_additive relindex_mul_index]
theorem relindex_mul_index (h : H ≤ K) : H.relindex K * K.index = H.index :=
((mul_comm _ _).trans (Cardinal.toNat_mul _ _).symm).trans
(congr_arg Cardinal.toNat (Equiv.cardinal_eq (quotientEquivProdOfLE h))).symm
@[to_additive]
theorem index_dvd_of_le (h : H ≤ K) : K.index ∣ H.index :=
dvd_of_mul_left_eq (H.relindex K) (relindex_mul_index h)
@[to_additive]
theorem relindex_dvd_index_of_le (h : H ≤ K) : H.relindex K ∣ H.index :=
dvd_of_mul_right_eq K.index (relindex_mul_index h)
@[to_additive]
theorem relindex_subgroupOf (hKL : K ≤ L) :
(H.subgroupOf L).relindex (K.subgroupOf L) = H.relindex K :=
((index_comap (H.subgroupOf L) (inclusion hKL)).trans (congr_arg _ (inclusion_range hKL))).symm
variable (H K L)
@[to_additive relindex_mul_relindex]
theorem relindex_mul_relindex (hHK : H ≤ K) (hKL : K ≤ L) :
H.relindex K * K.relindex L = H.relindex L := by
rw [← relindex_subgroupOf hKL]
exact relindex_mul_index fun x hx => hHK hx
@[to_additive]
theorem inf_relindex_right : (H ⊓ K).relindex K = H.relindex K := by
rw [relindex, relindex, inf_subgroupOf_right]
@[to_additive]
theorem inf_relindex_left : (H ⊓ K).relindex H = K.relindex H := by
rw [inf_comm, inf_relindex_right]
@[to_additive relindex_inf_mul_relindex]
theorem relindex_inf_mul_relindex : H.relindex (K ⊓ L) * K.relindex L = (H ⊓ K).relindex L := by
rw [← inf_relindex_right H (K ⊓ L), ← inf_relindex_right K L, ← inf_relindex_right (H ⊓ K) L,
inf_assoc, relindex_mul_relindex (H ⊓ (K ⊓ L)) (K ⊓ L) L inf_le_right inf_le_right]
@[to_additive (attr := simp)]
theorem relindex_sup_right [K.Normal] : K.relindex (H ⊔ K) = K.relindex H :=
Nat.card_congr (QuotientGroup.quotientInfEquivProdNormalQuotient H K).toEquiv.symm
@[to_additive (attr := simp)]
theorem relindex_sup_left [K.Normal] : K.relindex (K ⊔ H) = K.relindex H := by
rw [sup_comm, relindex_sup_right]
@[to_additive]
theorem relindex_dvd_index_of_normal [H.Normal] : H.relindex K ∣ H.index :=
relindex_sup_right K H ▸ relindex_dvd_index_of_le le_sup_right
variable {H K}
@[to_additive]
theorem relindex_dvd_of_le_left (hHK : H ≤ K) : K.relindex L ∣ H.relindex L :=
inf_of_le_left hHK ▸ dvd_of_mul_left_eq _ (relindex_inf_mul_relindex _ _ _)
/-- A subgroup has index two if and only if there exists `a` such that for all `b`, exactly one
of `b * a` and `b` belong to `H`. -/
@[to_additive "An additive subgroup has index two if and only if there exists `a` such that
for all `b`, exactly one of `b + a` and `b` belong to `H`."]
theorem index_eq_two_iff : H.index = 2 ↔ ∃ a, ∀ b, Xor' (b * a ∈ H) (b ∈ H) := by
simp only [index, Nat.card_eq_two_iff' ((1 : G) : G ⧸ H), ExistsUnique, inv_mem_iff,
QuotientGroup.exists_mk, QuotientGroup.forall_mk, Ne, QuotientGroup.eq, mul_one,
xor_iff_iff_not]
refine exists_congr fun a =>
⟨fun ha b => ⟨fun hba hb => ?_, fun hb => ?_⟩, fun ha => ⟨?_, fun b hb => ?_⟩⟩
· exact ha.1 ((mul_mem_cancel_left hb).1 hba)
· exact inv_inv b ▸ ha.2 _ (mt (inv_mem_iff (x := b)).1 hb)
· rw [← inv_mem_iff (x := a), ← ha, inv_mul_cancel]
exact one_mem _
· rwa [ha, inv_mem_iff (x := b)]
@[to_additive]
theorem mul_mem_iff_of_index_two (h : H.index = 2) {a b : G} : a * b ∈ H ↔ (a ∈ H ↔ b ∈ H) := by
by_cases ha : a ∈ H; · simp only [ha, true_iff, mul_mem_cancel_left ha]
by_cases hb : b ∈ H; · simp only [hb, iff_true, mul_mem_cancel_right hb]
simp only [ha, hb, iff_true]
rcases index_eq_two_iff.1 h with ⟨c, hc⟩
refine (hc _).or.resolve_left ?_
rwa [mul_assoc, mul_mem_cancel_right ((hc _).or.resolve_right hb)]
@[to_additive]
theorem mul_self_mem_of_index_two (h : H.index = 2) (a : G) : a * a ∈ H := by
rw [mul_mem_iff_of_index_two h]
@[to_additive two_smul_mem_of_index_two]
theorem sq_mem_of_index_two (h : H.index = 2) (a : G) : a ^ 2 ∈ H :=
(pow_two a).symm ▸ mul_self_mem_of_index_two h a
variable (H K) {f : G →* G'}
@[to_additive (attr := simp)]
theorem index_top : (⊤ : Subgroup G).index = 1 :=
Nat.card_eq_one_iff_unique.mpr ⟨QuotientGroup.subsingleton_quotient_top, ⟨1⟩⟩
@[to_additive (attr := simp)]
theorem index_bot : (⊥ : Subgroup G).index = Nat.card G :=
Cardinal.toNat_congr QuotientGroup.quotientBot.toEquiv
@[to_additive (attr := simp)]
theorem relindex_top_left : (⊤ : Subgroup G).relindex H = 1 :=
index_top
@[to_additive (attr := simp)]
theorem relindex_top_right : H.relindex ⊤ = H.index := by
rw [← relindex_mul_index (show H ≤ ⊤ from le_top), index_top, mul_one]
@[to_additive (attr := simp)]
theorem relindex_bot_left : (⊥ : Subgroup G).relindex H = Nat.card H := by
rw [relindex, bot_subgroupOf, index_bot]
@[to_additive (attr := simp)]
theorem relindex_bot_right : H.relindex ⊥ = 1 := by rw [relindex, subgroupOf_bot_eq_top, index_top]
@[to_additive (attr := simp)]
theorem relindex_self : H.relindex H = 1 := by rw [relindex, subgroupOf_self, index_top]
@[to_additive]
theorem index_ker (f : G →* G') : f.ker.index = Nat.card f.range := by
rw [← MonoidHom.comap_bot, index_comap, relindex_bot_left]
@[to_additive]
theorem relindex_ker (f : G →* G') : f.ker.relindex K = Nat.card (K.map f) := by
rw [← MonoidHom.comap_bot, relindex_comap, relindex_bot_left]
@[to_additive (attr := simp) card_mul_index]
theorem card_mul_index : Nat.card H * H.index = Nat.card G := by
rw [← relindex_bot_left, ← index_bot]
exact relindex_mul_index bot_le
@[to_additive]
theorem card_dvd_of_surjective (f : G →* G') (hf : Function.Surjective f) :
Nat.card G' ∣ Nat.card G := by
rw [← Nat.card_congr (QuotientGroup.quotientKerEquivOfSurjective f hf).toEquiv]
exact Dvd.intro_left (Nat.card f.ker) f.ker.card_mul_index
@[to_additive]
theorem card_range_dvd (f : G →* G') : Nat.card f.range ∣ Nat.card G :=
card_dvd_of_surjective f.rangeRestrict f.rangeRestrict_surjective
@[to_additive]
theorem card_map_dvd (f : G →* G') : Nat.card (H.map f) ∣ Nat.card H :=
card_dvd_of_surjective (f.subgroupMap H) (f.subgroupMap_surjective H)
@[to_additive]
theorem index_map (f : G →* G') :
(H.map f).index = (H ⊔ f.ker).index * f.range.index := by
rw [← comap_map_eq, index_comap, relindex_mul_index (H.map_le_range f)]
@[to_additive]
theorem index_map_dvd {f : G →* G'} (hf : Function.Surjective f) :
(H.map f).index ∣ H.index := by
rw [index_map, f.range_eq_top_of_surjective hf, index_top, mul_one]
exact index_dvd_of_le le_sup_left
@[to_additive]
theorem dvd_index_map {f : G →* G'} (hf : f.ker ≤ H) :
H.index ∣ (H.map f).index := by
rw [index_map, sup_of_le_left hf]
apply dvd_mul_right
@[to_additive]
theorem index_map_eq (hf1 : Surjective f) (hf2 : f.ker ≤ H) : (H.map f).index = H.index :=
Nat.dvd_antisymm (H.index_map_dvd hf1) (H.dvd_index_map hf2)
@[to_additive]
lemma index_map_of_bijective (hf : Bijective f) (H : Subgroup G) : (H.map f).index = H.index :=
index_map_eq _ hf.2 (by rw [f.ker_eq_bot_iff.2 hf.1]; exact bot_le)
@[to_additive]
theorem index_map_of_injective {f : G →* G'} (hf : Function.Injective f) :
(H.map f).index = H.index * f.range.index := by
rw [H.index_map, f.ker_eq_bot_iff.mpr hf, sup_bot_eq]
@[to_additive]
theorem index_map_subtype {H : Subgroup G} (K : Subgroup H) :
(K.map H.subtype).index = K.index * H.index := by
rw [K.index_map_of_injective H.subtype_injective, H.range_subtype]
@[to_additive]
theorem index_eq_card : H.index = Nat.card (G ⧸ H) :=
rfl
@[to_additive index_mul_card]
theorem index_mul_card : H.index * Nat.card H = Nat.card G := by
rw [mul_comm, card_mul_index]
@[to_additive]
theorem index_dvd_card : H.index ∣ Nat.card G :=
⟨Nat.card H, H.index_mul_card.symm⟩
@[to_additive]
theorem relindex_dvd_card : H.relindex K ∣ Nat.card K :=
(H.subgroupOf K).index_dvd_card
variable {H K L}
@[to_additive]
theorem relindex_eq_zero_of_le_left (hHK : H ≤ K) (hKL : K.relindex L = 0) : H.relindex L = 0 :=
eq_zero_of_zero_dvd (hKL ▸ relindex_dvd_of_le_left L hHK)
@[to_additive]
theorem relindex_eq_zero_of_le_right (hKL : K ≤ L) (hHK : H.relindex K = 0) : H.relindex L = 0 :=
Finite.card_eq_zero_of_embedding (quotientSubgroupOfEmbeddingOfLE H hKL) hHK
@[to_additive]
theorem index_eq_zero_of_relindex_eq_zero (h : H.relindex K = 0) : H.index = 0 :=
H.relindex_top_right.symm.trans (relindex_eq_zero_of_le_right le_top h)
@[to_additive]
theorem relindex_le_of_le_left (hHK : H ≤ K) (hHL : H.relindex L ≠ 0) :
K.relindex L ≤ H.relindex L :=
Nat.le_of_dvd (Nat.pos_of_ne_zero hHL) (relindex_dvd_of_le_left L hHK)
@[to_additive]
theorem relindex_le_of_le_right (hKL : K ≤ L) (hHL : H.relindex L ≠ 0) :
H.relindex K ≤ H.relindex L :=
Finite.card_le_of_embedding' (quotientSubgroupOfEmbeddingOfLE H hKL) fun h => (hHL h).elim
@[to_additive]
theorem relindex_ne_zero_trans (hHK : H.relindex K ≠ 0) (hKL : K.relindex L ≠ 0) :
H.relindex L ≠ 0 := fun h =>
mul_ne_zero (mt (relindex_eq_zero_of_le_right (show K ⊓ L ≤ K from inf_le_left)) hHK) hKL
((relindex_inf_mul_relindex H K L).trans (relindex_eq_zero_of_le_left inf_le_left h))
@[to_additive]
theorem relindex_inf_ne_zero (hH : H.relindex L ≠ 0) (hK : K.relindex L ≠ 0) :
(H ⊓ K).relindex L ≠ 0 := by
replace hH : H.relindex (K ⊓ L) ≠ 0 := mt (relindex_eq_zero_of_le_right inf_le_right) hH
rw [← inf_relindex_right] at hH hK ⊢
rw [inf_assoc]
exact relindex_ne_zero_trans hH hK
@[to_additive]
| Mathlib/GroupTheory/Index.lean | 326 | 328 | theorem index_inf_ne_zero (hH : H.index ≠ 0) (hK : K.index ≠ 0) : (H ⊓ K).index ≠ 0 := by | rw [← relindex_top_right] at hH hK ⊢
exact relindex_inf_ne_zero hH hK |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Kim Morrison, Jens Wagemaker
-/
import Mathlib.Algebra.Polynomial.Degree.Domain
import Mathlib.Algebra.Polynomial.Degree.Support
import Mathlib.Algebra.Polynomial.Eval.Coeff
import Mathlib.GroupTheory.GroupAction.Ring
/-!
# The derivative map on polynomials
## Main definitions
* `Polynomial.derivative`: The formal derivative of polynomials, expressed as a linear map.
* `Polynomial.derivativeFinsupp`: Iterated derivatives as a finite support function.
-/
noncomputable section
open Finset
open Polynomial
open scoped Nat
namespace Polynomial
universe u v w y z
variable {R : Type u} {S : Type v} {T : Type w} {ι : Type y} {A : Type z} {a b : R} {n : ℕ}
section Derivative
section Semiring
variable [Semiring R]
/-- `derivative p` is the formal derivative of the polynomial `p` -/
def derivative : R[X] →ₗ[R] R[X] where
toFun p := p.sum fun n a => C (a * n) * X ^ (n - 1)
map_add' p q := by
rw [sum_add_index] <;>
simp only [add_mul, forall_const, RingHom.map_add, eq_self_iff_true, zero_mul,
RingHom.map_zero]
map_smul' a p := by
dsimp; rw [sum_smul_index] <;>
simp only [mul_sum, ← C_mul', mul_assoc, coeff_C_mul, RingHom.map_mul, forall_const, zero_mul,
RingHom.map_zero, sum]
theorem derivative_apply (p : R[X]) : derivative p = p.sum fun n a => C (a * n) * X ^ (n - 1) :=
rfl
theorem coeff_derivative (p : R[X]) (n : ℕ) :
coeff (derivative p) n = coeff p (n + 1) * (n + 1) := by
rw [derivative_apply]
simp only [coeff_X_pow, coeff_sum, coeff_C_mul]
rw [sum, Finset.sum_eq_single (n + 1)]
· simp only [Nat.add_succ_sub_one, add_zero, mul_one, if_true, eq_self_iff_true]; norm_cast
· intro b
cases b
· intros
rw [Nat.cast_zero, mul_zero, zero_mul]
· intro _ H
rw [Nat.add_one_sub_one, if_neg (mt (congr_arg Nat.succ) H.symm), mul_zero]
· rw [if_pos (add_tsub_cancel_right n 1).symm, mul_one, Nat.cast_add, Nat.cast_one,
mem_support_iff]
intro h
push_neg at h
simp [h]
@[simp]
theorem derivative_zero : derivative (0 : R[X]) = 0 :=
derivative.map_zero
theorem iterate_derivative_zero {k : ℕ} : derivative^[k] (0 : R[X]) = 0 :=
iterate_map_zero derivative k
theorem derivative_monomial (a : R) (n : ℕ) :
derivative (monomial n a) = monomial (n - 1) (a * n) := by
rw [derivative_apply, sum_monomial_index, C_mul_X_pow_eq_monomial]
simp
@[simp]
theorem derivative_monomial_succ (a : R) (n : ℕ) :
derivative (monomial (n + 1) a) = monomial n (a * (n + 1)) := by
rw [derivative_monomial, add_tsub_cancel_right, Nat.cast_add, Nat.cast_one]
theorem derivative_C_mul_X (a : R) : derivative (C a * X) = C a := by
simp [C_mul_X_eq_monomial, derivative_monomial, Nat.cast_one, mul_one]
theorem derivative_C_mul_X_pow (a : R) (n : ℕ) :
derivative (C a * X ^ n) = C (a * n) * X ^ (n - 1) := by
rw [C_mul_X_pow_eq_monomial, C_mul_X_pow_eq_monomial, derivative_monomial]
theorem derivative_C_mul_X_sq (a : R) : derivative (C a * X ^ 2) = C (a * 2) * X := by
rw [derivative_C_mul_X_pow, Nat.cast_two, pow_one]
theorem derivative_X_pow (n : ℕ) : derivative (X ^ n : R[X]) = C (n : R) * X ^ (n - 1) := by
convert derivative_C_mul_X_pow (1 : R) n <;> simp
@[simp]
theorem derivative_X_pow_succ (n : ℕ) :
derivative (X ^ (n + 1) : R[X]) = C (n + 1 : R) * X ^ n := by
simp [derivative_X_pow]
theorem derivative_X_sq : derivative (X ^ 2 : R[X]) = C 2 * X := by
rw [derivative_X_pow, Nat.cast_two, pow_one]
@[simp]
theorem derivative_C {a : R} : derivative (C a) = 0 := by simp [derivative_apply]
| Mathlib/Algebra/Polynomial/Derivative.lean | 115 | 116 | theorem derivative_of_natDegree_zero {p : R[X]} (hp : p.natDegree = 0) : derivative p = 0 := by | rw [eq_C_of_natDegree_eq_zero hp, derivative_C] |
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Johannes Hölzl
-/
import Mathlib.Algebra.Order.Pi
import Mathlib.MeasureTheory.Constructions.BorelSpace.Order
/-!
# Simple functions
A function `f` from a measurable space to any type is called *simple*, if every preimage `f ⁻¹' {x}`
is measurable, and the range is finite. In this file, we define simple functions and establish their
basic properties; and we construct a sequence of simple functions approximating an arbitrary Borel
measurable function `f : α → ℝ≥0∞`.
The theorem `Measurable.ennreal_induction` shows that in order to prove something for an arbitrary
measurable function into `ℝ≥0∞`, it is sufficient to show that the property holds for (multiples of)
characteristic functions and is closed under addition and supremum of increasing sequences of
functions.
-/
noncomputable section
open Set hiding restrict restrict_apply
open Filter ENNReal
open Function (support)
open Topology NNReal ENNReal MeasureTheory
namespace MeasureTheory
variable {α β γ δ : Type*}
/-- A function `f` from a measurable space to any type is called *simple*,
if every preimage `f ⁻¹' {x}` is measurable, and the range is finite. This structure bundles
a function with these properties. -/
structure SimpleFunc.{u, v} (α : Type u) [MeasurableSpace α] (β : Type v) where
/-- The underlying function -/
toFun : α → β
measurableSet_fiber' : ∀ x, MeasurableSet (toFun ⁻¹' {x})
finite_range' : (Set.range toFun).Finite
local infixr:25 " →ₛ " => SimpleFunc
namespace SimpleFunc
section Measurable
variable [MeasurableSpace α]
instance instFunLike : FunLike (α →ₛ β) α β where
coe := toFun
coe_injective' | ⟨_, _, _⟩, ⟨_, _, _⟩, rfl => rfl
theorem coe_injective ⦃f g : α →ₛ β⦄ (H : (f : α → β) = g) : f = g := DFunLike.ext' H
@[ext]
theorem ext {f g : α →ₛ β} (H : ∀ a, f a = g a) : f = g := DFunLike.ext _ _ H
theorem finite_range (f : α →ₛ β) : (Set.range f).Finite :=
f.finite_range'
theorem measurableSet_fiber (f : α →ₛ β) (x : β) : MeasurableSet (f ⁻¹' {x}) :=
f.measurableSet_fiber' x
@[simp] theorem coe_mk (f : α → β) (h h') : ⇑(mk f h h') = f := rfl
theorem apply_mk (f : α → β) (h h') (x : α) : SimpleFunc.mk f h h' x = f x :=
rfl
/-- Simple function defined on a finite type. -/
def ofFinite [Finite α] [MeasurableSingletonClass α] (f : α → β) : α →ₛ β where
toFun := f
measurableSet_fiber' x := (toFinite (f ⁻¹' {x})).measurableSet
finite_range' := Set.finite_range f
/-- Simple function defined on the empty type. -/
def ofIsEmpty [IsEmpty α] : α →ₛ β := ofFinite isEmptyElim
/-- Range of a simple function `α →ₛ β` as a `Finset β`. -/
protected def range (f : α →ₛ β) : Finset β :=
f.finite_range.toFinset
@[simp]
theorem mem_range {f : α →ₛ β} {b} : b ∈ f.range ↔ b ∈ range f :=
Finite.mem_toFinset _
theorem mem_range_self (f : α →ₛ β) (x : α) : f x ∈ f.range :=
mem_range.2 ⟨x, rfl⟩
@[simp]
theorem coe_range (f : α →ₛ β) : (↑f.range : Set β) = Set.range f :=
f.finite_range.coe_toFinset
theorem mem_range_of_measure_ne_zero {f : α →ₛ β} {x : β} {μ : Measure α} (H : μ (f ⁻¹' {x}) ≠ 0) :
x ∈ f.range :=
let ⟨a, ha⟩ := nonempty_of_measure_ne_zero H
mem_range.2 ⟨a, ha⟩
theorem forall_mem_range {f : α →ₛ β} {p : β → Prop} : (∀ y ∈ f.range, p y) ↔ ∀ x, p (f x) := by
simp only [mem_range, Set.forall_mem_range]
theorem exists_range_iff {f : α →ₛ β} {p : β → Prop} : (∃ y ∈ f.range, p y) ↔ ∃ x, p (f x) := by
simpa only [mem_range, exists_prop] using Set.exists_range_iff
theorem preimage_eq_empty_iff (f : α →ₛ β) (b : β) : f ⁻¹' {b} = ∅ ↔ b ∉ f.range :=
preimage_singleton_eq_empty.trans <| not_congr mem_range.symm
theorem exists_forall_le [Nonempty β] [Preorder β] [IsDirected β (· ≤ ·)] (f : α →ₛ β) :
∃ C, ∀ x, f x ≤ C :=
f.range.exists_le.imp fun _ => forall_mem_range.1
/-- Constant function as a `SimpleFunc`. -/
def const (α) {β} [MeasurableSpace α] (b : β) : α →ₛ β :=
⟨fun _ => b, fun _ => MeasurableSet.const _, finite_range_const⟩
instance instInhabited [Inhabited β] : Inhabited (α →ₛ β) :=
⟨const _ default⟩
theorem const_apply (a : α) (b : β) : (const α b) a = b :=
rfl
@[simp]
theorem coe_const (b : β) : ⇑(const α b) = Function.const α b :=
rfl
@[simp]
theorem range_const (α) [MeasurableSpace α] [Nonempty α] (b : β) : (const α b).range = {b} :=
Finset.coe_injective <| by simp +unfoldPartialApp [Function.const]
theorem range_const_subset (α) [MeasurableSpace α] (b : β) : (const α b).range ⊆ {b} :=
Finset.coe_subset.1 <| by simp
theorem simpleFunc_bot {α} (f : @SimpleFunc α ⊥ β) [Nonempty β] : ∃ c, ∀ x, f x = c := by
have hf_meas := @SimpleFunc.measurableSet_fiber α _ ⊥ f
simp_rw [MeasurableSpace.measurableSet_bot_iff] at hf_meas
exact (exists_eq_const_of_preimage_singleton hf_meas).imp fun c hc ↦ congr_fun hc
theorem simpleFunc_bot' {α} [Nonempty β] (f : @SimpleFunc α ⊥ β) :
∃ c, f = @SimpleFunc.const α _ ⊥ c :=
letI : MeasurableSpace α := ⊥; (simpleFunc_bot f).imp fun _ ↦ ext
theorem measurableSet_cut (r : α → β → Prop) (f : α →ₛ β) (h : ∀ b, MeasurableSet { a | r a b }) :
MeasurableSet { a | r a (f a) } := by
have : { a | r a (f a) } = ⋃ b ∈ range f, { a | r a b } ∩ f ⁻¹' {b} := by
ext a
suffices r a (f a) ↔ ∃ i, r a (f i) ∧ f a = f i by simpa
exact ⟨fun h => ⟨a, ⟨h, rfl⟩⟩, fun ⟨a', ⟨h', e⟩⟩ => e.symm ▸ h'⟩
rw [this]
exact
MeasurableSet.biUnion f.finite_range.countable fun b _ =>
MeasurableSet.inter (h b) (f.measurableSet_fiber _)
@[measurability]
theorem measurableSet_preimage (f : α →ₛ β) (s) : MeasurableSet (f ⁻¹' s) :=
measurableSet_cut (fun _ b => b ∈ s) f fun b => MeasurableSet.const (b ∈ s)
/-- A simple function is measurable -/
@[measurability, fun_prop]
protected theorem measurable [MeasurableSpace β] (f : α →ₛ β) : Measurable f := fun s _ =>
measurableSet_preimage f s
@[measurability]
protected theorem aemeasurable [MeasurableSpace β] {μ : Measure α} (f : α →ₛ β) :
AEMeasurable f μ :=
f.measurable.aemeasurable
protected theorem sum_measure_preimage_singleton (f : α →ₛ β) {μ : Measure α} (s : Finset β) :
(∑ y ∈ s, μ (f ⁻¹' {y})) = μ (f ⁻¹' ↑s) :=
sum_measure_preimage_singleton _ fun _ _ => f.measurableSet_fiber _
theorem sum_range_measure_preimage_singleton (f : α →ₛ β) (μ : Measure α) :
(∑ y ∈ f.range, μ (f ⁻¹' {y})) = μ univ := by
rw [f.sum_measure_preimage_singleton, coe_range, preimage_range]
open scoped Classical in
/-- If-then-else as a `SimpleFunc`. -/
def piecewise (s : Set α) (hs : MeasurableSet s) (f g : α →ₛ β) : α →ₛ β :=
⟨s.piecewise f g, fun _ =>
letI : MeasurableSpace β := ⊤
f.measurable.piecewise hs g.measurable trivial,
(f.finite_range.union g.finite_range).subset range_ite_subset⟩
open scoped Classical in
@[simp]
theorem coe_piecewise {s : Set α} (hs : MeasurableSet s) (f g : α →ₛ β) :
⇑(piecewise s hs f g) = s.piecewise f g :=
rfl
open scoped Classical in
theorem piecewise_apply {s : Set α} (hs : MeasurableSet s) (f g : α →ₛ β) (a) :
piecewise s hs f g a = if a ∈ s then f a else g a :=
rfl
open scoped Classical in
@[simp]
theorem piecewise_compl {s : Set α} (hs : MeasurableSet sᶜ) (f g : α →ₛ β) :
piecewise sᶜ hs f g = piecewise s hs.of_compl g f :=
coe_injective <| by simp [hs]
@[simp]
theorem piecewise_univ (f g : α →ₛ β) : piecewise univ MeasurableSet.univ f g = f :=
coe_injective <| by simp
@[simp]
theorem piecewise_empty (f g : α →ₛ β) : piecewise ∅ MeasurableSet.empty f g = g :=
coe_injective <| by simp
open scoped Classical in
@[simp]
theorem piecewise_same (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) :
piecewise s hs f f = f :=
coe_injective <| Set.piecewise_same _ _
theorem support_indicator [Zero β] {s : Set α} (hs : MeasurableSet s) (f : α →ₛ β) :
Function.support (f.piecewise s hs (SimpleFunc.const α 0)) = s ∩ Function.support f :=
Set.support_indicator
open scoped Classical in
theorem range_indicator {s : Set α} (hs : MeasurableSet s) (hs_nonempty : s.Nonempty)
(hs_ne_univ : s ≠ univ) (x y : β) :
(piecewise s hs (const α x) (const α y)).range = {x, y} := by
simp only [← Finset.coe_inj, coe_range, coe_piecewise, range_piecewise, coe_const,
Finset.coe_insert, Finset.coe_singleton, hs_nonempty.image_const,
(nonempty_compl.2 hs_ne_univ).image_const, singleton_union, Function.const]
theorem measurable_bind [MeasurableSpace γ] (f : α →ₛ β) (g : β → α → γ)
(hg : ∀ b, Measurable (g b)) : Measurable fun a => g (f a) a := fun s hs =>
f.measurableSet_cut (fun a b => g b a ∈ s) fun b => hg b hs
/-- If `f : α →ₛ β` is a simple function and `g : β → α →ₛ γ` is a family of simple functions,
then `f.bind g` binds the first argument of `g` to `f`. In other words, `f.bind g a = g (f a) a`. -/
def bind (f : α →ₛ β) (g : β → α →ₛ γ) : α →ₛ γ :=
⟨fun a => g (f a) a, fun c =>
f.measurableSet_cut (fun a b => g b a = c) fun b => (g b).measurableSet_preimage {c},
(f.finite_range.biUnion fun b _ => (g b).finite_range).subset <| by
rintro _ ⟨a, rfl⟩; simp⟩
@[simp]
theorem bind_apply (f : α →ₛ β) (g : β → α →ₛ γ) (a) : f.bind g a = g (f a) a :=
rfl
/-- Given a function `g : β → γ` and a simple function `f : α →ₛ β`, `f.map g` return the simple
function `g ∘ f : α →ₛ γ` -/
def map (g : β → γ) (f : α →ₛ β) : α →ₛ γ :=
bind f (const α ∘ g)
theorem map_apply (g : β → γ) (f : α →ₛ β) (a) : f.map g a = g (f a) :=
rfl
theorem map_map (g : β → γ) (h : γ → δ) (f : α →ₛ β) : (f.map g).map h = f.map (h ∘ g) :=
rfl
@[simp]
theorem coe_map (g : β → γ) (f : α →ₛ β) : (f.map g : α → γ) = g ∘ f :=
rfl
@[simp]
theorem range_map [DecidableEq γ] (g : β → γ) (f : α →ₛ β) : (f.map g).range = f.range.image g :=
Finset.coe_injective <| by simp only [coe_range, coe_map, Finset.coe_image, range_comp]
@[simp]
theorem map_const (g : β → γ) (b : β) : (const α b).map g = const α (g b) :=
rfl
open scoped Classical in
theorem map_preimage (f : α →ₛ β) (g : β → γ) (s : Set γ) :
f.map g ⁻¹' s = f ⁻¹' ↑{b ∈ f.range | g b ∈ s} := by
simp only [coe_range, sep_mem_eq, coe_map, Finset.coe_filter,
← mem_preimage, inter_comm, preimage_inter_range, ← Finset.mem_coe]
exact preimage_comp
open scoped Classical in
theorem map_preimage_singleton (f : α →ₛ β) (g : β → γ) (c : γ) :
f.map g ⁻¹' {c} = f ⁻¹' ↑{b ∈ f.range | g b = c} :=
map_preimage _ _ _
/-- Composition of a `SimpleFun` and a measurable function is a `SimpleFunc`. -/
def comp [MeasurableSpace β] (f : β →ₛ γ) (g : α → β) (hgm : Measurable g) : α →ₛ γ where
toFun := f ∘ g
finite_range' := f.finite_range.subset <| Set.range_comp_subset_range _ _
measurableSet_fiber' z := hgm (f.measurableSet_fiber z)
@[simp]
theorem coe_comp [MeasurableSpace β] (f : β →ₛ γ) {g : α → β} (hgm : Measurable g) :
⇑(f.comp g hgm) = f ∘ g :=
rfl
theorem range_comp_subset_range [MeasurableSpace β] (f : β →ₛ γ) {g : α → β} (hgm : Measurable g) :
(f.comp g hgm).range ⊆ f.range :=
Finset.coe_subset.1 <| by simp only [coe_range, coe_comp, Set.range_comp_subset_range]
/-- Extend a `SimpleFunc` along a measurable embedding: `f₁.extend g hg f₂` is the function
`F : β →ₛ γ` such that `F ∘ g = f₁` and `F y = f₂ y` whenever `y ∉ range g`. -/
def extend [MeasurableSpace β] (f₁ : α →ₛ γ) (g : α → β) (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) : β →ₛ γ where
toFun := Function.extend g f₁ f₂
finite_range' :=
(f₁.finite_range.union <| f₂.finite_range.subset (image_subset_range _ _)).subset
(range_extend_subset _ _ _)
measurableSet_fiber' := by
letI : MeasurableSpace γ := ⊤; haveI : MeasurableSingletonClass γ := ⟨fun _ => trivial⟩
exact fun x => hg.measurable_extend f₁.measurable f₂.measurable (measurableSet_singleton _)
@[simp]
theorem extend_apply [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) (x : α) : (f₁.extend g hg f₂) (g x) = f₁ x :=
hg.injective.extend_apply _ _ _
@[simp]
theorem extend_apply' [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) {y : β} (h : ¬∃ x, g x = y) : (f₁.extend g hg f₂) y = f₂ y :=
Function.extend_apply' _ _ _ h
@[simp]
theorem extend_comp_eq' [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) : f₁.extend g hg f₂ ∘ g = f₁ :=
funext fun _ => extend_apply _ _ _ _
@[simp]
theorem extend_comp_eq [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) : (f₁.extend g hg f₂).comp g hg.measurable = f₁ :=
coe_injective <| extend_comp_eq' _ hg _
/-- If `f` is a simple function taking values in `β → γ` and `g` is another simple function
with the same domain and codomain `β`, then `f.seq g = f a (g a)`. -/
def seq (f : α →ₛ β → γ) (g : α →ₛ β) : α →ₛ γ :=
f.bind fun f => g.map f
@[simp]
theorem seq_apply (f : α →ₛ β → γ) (g : α →ₛ β) (a : α) : f.seq g a = f a (g a) :=
rfl
/-- Combine two simple functions `f : α →ₛ β` and `g : α →ₛ β`
into `fun a => (f a, g a)`. -/
def pair (f : α →ₛ β) (g : α →ₛ γ) : α →ₛ β × γ :=
(f.map Prod.mk).seq g
@[simp]
theorem pair_apply (f : α →ₛ β) (g : α →ₛ γ) (a) : pair f g a = (f a, g a) :=
rfl
theorem pair_preimage (f : α →ₛ β) (g : α →ₛ γ) (s : Set β) (t : Set γ) :
pair f g ⁻¹' s ×ˢ t = f ⁻¹' s ∩ g ⁻¹' t :=
rfl
-- A special form of `pair_preimage`
theorem pair_preimage_singleton (f : α →ₛ β) (g : α →ₛ γ) (b : β) (c : γ) :
pair f g ⁻¹' {(b, c)} = f ⁻¹' {b} ∩ g ⁻¹' {c} := by
rw [← singleton_prod_singleton]
exact pair_preimage _ _ _ _
@[simp] theorem map_fst_pair (f : α →ₛ β) (g : α →ₛ γ) : (f.pair g).map Prod.fst = f := rfl
@[simp] theorem map_snd_pair (f : α →ₛ β) (g : α →ₛ γ) : (f.pair g).map Prod.snd = g := rfl
@[simp]
theorem bind_const (f : α →ₛ β) : f.bind (const α) = f := by ext; simp
@[to_additive]
instance instOne [One β] : One (α →ₛ β) :=
⟨const α 1⟩
@[to_additive]
instance instMul [Mul β] : Mul (α →ₛ β) :=
⟨fun f g => (f.map (· * ·)).seq g⟩
@[to_additive]
instance instDiv [Div β] : Div (α →ₛ β) :=
⟨fun f g => (f.map (· / ·)).seq g⟩
@[to_additive]
instance instInv [Inv β] : Inv (α →ₛ β) :=
⟨fun f => f.map Inv.inv⟩
instance instSup [Max β] : Max (α →ₛ β) :=
⟨fun f g => (f.map (· ⊔ ·)).seq g⟩
instance instInf [Min β] : Min (α →ₛ β) :=
⟨fun f g => (f.map (· ⊓ ·)).seq g⟩
instance instLE [LE β] : LE (α →ₛ β) :=
⟨fun f g => ∀ a, f a ≤ g a⟩
@[to_additive (attr := simp)]
theorem const_one [One β] : const α (1 : β) = 1 :=
rfl
@[to_additive (attr := simp, norm_cast)]
theorem coe_one [One β] : ⇑(1 : α →ₛ β) = 1 :=
rfl
@[to_additive (attr := simp, norm_cast)]
theorem coe_mul [Mul β] (f g : α →ₛ β) : ⇑(f * g) = ⇑f * ⇑g :=
rfl
@[to_additive (attr := simp, norm_cast)]
theorem coe_inv [Inv β] (f : α →ₛ β) : ⇑(f⁻¹) = (⇑f)⁻¹ :=
rfl
@[to_additive (attr := simp, norm_cast)]
theorem coe_div [Div β] (f g : α →ₛ β) : ⇑(f / g) = ⇑f / ⇑g :=
rfl
@[simp, norm_cast]
theorem coe_le [LE β] {f g : α →ₛ β} : (f : α → β) ≤ g ↔ f ≤ g :=
Iff.rfl
@[simp, norm_cast]
theorem coe_sup [Max β] (f g : α →ₛ β) : ⇑(f ⊔ g) = ⇑f ⊔ ⇑g :=
rfl
@[simp, norm_cast]
theorem coe_inf [Min β] (f g : α →ₛ β) : ⇑(f ⊓ g) = ⇑f ⊓ ⇑g :=
rfl
@[to_additive]
theorem mul_apply [Mul β] (f g : α →ₛ β) (a : α) : (f * g) a = f a * g a :=
rfl
@[to_additive]
theorem div_apply [Div β] (f g : α →ₛ β) (x : α) : (f / g) x = f x / g x :=
rfl
@[to_additive]
theorem inv_apply [Inv β] (f : α →ₛ β) (x : α) : f⁻¹ x = (f x)⁻¹ :=
rfl
theorem sup_apply [Max β] (f g : α →ₛ β) (a : α) : (f ⊔ g) a = f a ⊔ g a :=
rfl
theorem inf_apply [Min β] (f g : α →ₛ β) (a : α) : (f ⊓ g) a = f a ⊓ g a :=
rfl
@[to_additive (attr := simp)]
theorem range_one [Nonempty α] [One β] : (1 : α →ₛ β).range = {1} :=
Finset.ext fun x => by simp [eq_comm]
@[simp]
theorem range_eq_empty_of_isEmpty {β} [hα : IsEmpty α] (f : α →ₛ β) : f.range = ∅ := by
rw [← Finset.not_nonempty_iff_eq_empty]
by_contra h
obtain ⟨y, hy_mem⟩ := h
rw [SimpleFunc.mem_range, Set.mem_range] at hy_mem
obtain ⟨x, hxy⟩ := hy_mem
rw [isEmpty_iff] at hα
exact hα x
theorem eq_zero_of_mem_range_zero [Zero β] : ∀ {y : β}, y ∈ (0 : α →ₛ β).range → y = 0 :=
@(forall_mem_range.2 fun _ => rfl)
@[to_additive]
theorem mul_eq_map₂ [Mul β] (f g : α →ₛ β) : f * g = (pair f g).map fun p : β × β => p.1 * p.2 :=
rfl
theorem sup_eq_map₂ [Max β] (f g : α →ₛ β) : f ⊔ g = (pair f g).map fun p : β × β => p.1 ⊔ p.2 :=
rfl
@[to_additive]
theorem const_mul_eq_map [Mul β] (f : α →ₛ β) (b : β) : const α b * f = f.map fun a => b * a :=
rfl
@[to_additive]
theorem map_mul [Mul β] [Mul γ] {g : β → γ} (hg : ∀ x y, g (x * y) = g x * g y) (f₁ f₂ : α →ₛ β) :
(f₁ * f₂).map g = f₁.map g * f₂.map g :=
ext fun _ => hg _ _
variable {K : Type*}
@[to_additive]
instance instSMul [SMul K β] : SMul K (α →ₛ β) :=
⟨fun k f => f.map (k • ·)⟩
@[to_additive (attr := simp)]
theorem coe_smul [SMul K β] (c : K) (f : α →ₛ β) : ⇑(c • f) = c • ⇑f :=
rfl
@[to_additive (attr := simp)]
theorem smul_apply [SMul K β] (k : K) (f : α →ₛ β) (a : α) : (k • f) a = k • f a :=
rfl
instance hasNatSMul [AddMonoid β] : SMul ℕ (α →ₛ β) := inferInstance
@[to_additive existing hasNatSMul]
instance hasNatPow [Monoid β] : Pow (α →ₛ β) ℕ :=
⟨fun f n => f.map (· ^ n)⟩
@[simp]
theorem coe_pow [Monoid β] (f : α →ₛ β) (n : ℕ) : ⇑(f ^ n) = (⇑f) ^ n :=
rfl
theorem pow_apply [Monoid β] (n : ℕ) (f : α →ₛ β) (a : α) : (f ^ n) a = f a ^ n :=
rfl
instance hasIntPow [DivInvMonoid β] : Pow (α →ₛ β) ℤ :=
⟨fun f n => f.map (· ^ n)⟩
@[simp]
theorem coe_zpow [DivInvMonoid β] (f : α →ₛ β) (z : ℤ) : ⇑(f ^ z) = (⇑f) ^ z :=
rfl
theorem zpow_apply [DivInvMonoid β] (z : ℤ) (f : α →ₛ β) (a : α) : (f ^ z) a = f a ^ z :=
rfl
-- TODO: work out how to generate these instances with `to_additive`, which gets confused by the
-- argument order swap between `coe_smul` and `coe_pow`.
section Additive
instance instAddMonoid [AddMonoid β] : AddMonoid (α →ₛ β) :=
Function.Injective.addMonoid (fun f => show α → β from f) coe_injective coe_zero coe_add
fun _ _ => coe_smul _ _
instance instAddCommMonoid [AddCommMonoid β] : AddCommMonoid (α →ₛ β) :=
Function.Injective.addCommMonoid (fun f => show α → β from f) coe_injective coe_zero coe_add
fun _ _ => coe_smul _ _
instance instAddGroup [AddGroup β] : AddGroup (α →ₛ β) :=
Function.Injective.addGroup (fun f => show α → β from f) coe_injective coe_zero coe_add coe_neg
coe_sub (fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
instance instAddCommGroup [AddCommGroup β] : AddCommGroup (α →ₛ β) :=
Function.Injective.addCommGroup (fun f => show α → β from f) coe_injective coe_zero coe_add
coe_neg coe_sub (fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
end Additive
@[to_additive existing]
instance instMonoid [Monoid β] : Monoid (α →ₛ β) :=
Function.Injective.monoid (fun f => show α → β from f) coe_injective coe_one coe_mul coe_pow
@[to_additive existing]
instance instCommMonoid [CommMonoid β] : CommMonoid (α →ₛ β) :=
Function.Injective.commMonoid (fun f => show α → β from f) coe_injective coe_one coe_mul coe_pow
@[to_additive existing]
instance instGroup [Group β] : Group (α →ₛ β) :=
Function.Injective.group (fun f => show α → β from f) coe_injective coe_one coe_mul coe_inv
coe_div coe_pow coe_zpow
@[to_additive existing]
instance instCommGroup [CommGroup β] : CommGroup (α →ₛ β) :=
Function.Injective.commGroup (fun f => show α → β from f) coe_injective coe_one coe_mul coe_inv
coe_div coe_pow coe_zpow
instance instModule [Semiring K] [AddCommMonoid β] [Module K β] : Module K (α →ₛ β) :=
Function.Injective.module K ⟨⟨fun f => show α → β from f, coe_zero⟩, coe_add⟩
coe_injective coe_smul
theorem smul_eq_map [SMul K β] (k : K) (f : α →ₛ β) : k • f = f.map (k • ·) :=
rfl
section Preorder
variable [Preorder β] {s : Set α} {f f₁ f₂ g g₁ g₂ : α →ₛ β} {hs : MeasurableSet s}
instance instPreorder : Preorder (α →ₛ β) := Preorder.lift (⇑)
@[norm_cast] lemma coe_le_coe : ⇑f ≤ g ↔ f ≤ g := .rfl
@[simp, norm_cast] lemma coe_lt_coe : ⇑f < g ↔ f < g := .rfl
@[simp] lemma mk_le_mk {f g : α → β} {hf hg hf' hg'} : mk f hf hf' ≤ mk g hg hg' ↔ f ≤ g := Iff.rfl
@[simp] lemma mk_lt_mk {f g : α → β} {hf hg hf' hg'} : mk f hf hf' < mk g hg hg' ↔ f < g := Iff.rfl
@[gcongr] protected alias ⟨_, GCongr.mk_le_mk⟩ := mk_le_mk
@[gcongr] protected alias ⟨_, GCongr.mk_lt_mk⟩ := mk_lt_mk
@[gcongr] protected alias ⟨_, GCongr.coe_le_coe⟩ := coe_le_coe
@[gcongr] protected alias ⟨_, GCongr.coe_lt_coe⟩ := coe_lt_coe
open scoped Classical in
@[gcongr]
lemma piecewise_mono (hf : ∀ a ∈ s, f₁ a ≤ f₂ a) (hg : ∀ a ∉ s, g₁ a ≤ g₂ a) :
piecewise s hs f₁ g₁ ≤ piecewise s hs f₂ g₂ := Set.piecewise_mono hf hg
end Preorder
instance instPartialOrder [PartialOrder β] : PartialOrder (α →ₛ β) :=
{ SimpleFunc.instPreorder with
le_antisymm := fun _f _g hfg hgf => ext fun a => le_antisymm (hfg a) (hgf a) }
instance instOrderBot [LE β] [OrderBot β] : OrderBot (α →ₛ β) where
bot := const α ⊥
bot_le _ _ := bot_le
instance instOrderTop [LE β] [OrderTop β] : OrderTop (α →ₛ β) where
top := const α ⊤
le_top _ _ := le_top
@[to_additive]
instance [CommMonoid β] [PartialOrder β] [IsOrderedMonoid β] :
IsOrderedMonoid (α →ₛ β) where
mul_le_mul_left _ _ h _ _ := mul_le_mul_left' (h _) _
instance instSemilatticeInf [SemilatticeInf β] : SemilatticeInf (α →ₛ β) :=
{ SimpleFunc.instPartialOrder with
inf := (· ⊓ ·)
inf_le_left := fun _ _ _ => inf_le_left
inf_le_right := fun _ _ _ => inf_le_right
le_inf := fun _f _g _h hfh hgh a => le_inf (hfh a) (hgh a) }
instance instSemilatticeSup [SemilatticeSup β] : SemilatticeSup (α →ₛ β) :=
{ SimpleFunc.instPartialOrder with
sup := (· ⊔ ·)
le_sup_left := fun _ _ _ => le_sup_left
le_sup_right := fun _ _ _ => le_sup_right
sup_le := fun _f _g _h hfh hgh a => sup_le (hfh a) (hgh a) }
instance instLattice [Lattice β] : Lattice (α →ₛ β) :=
{ SimpleFunc.instSemilatticeSup, SimpleFunc.instSemilatticeInf with }
instance instBoundedOrder [LE β] [BoundedOrder β] : BoundedOrder (α →ₛ β) :=
{ SimpleFunc.instOrderBot, SimpleFunc.instOrderTop with }
theorem finset_sup_apply [SemilatticeSup β] [OrderBot β] {f : γ → α →ₛ β} (s : Finset γ) (a : α) :
s.sup f a = s.sup fun c => f c a := by
classical
refine Finset.induction_on s rfl ?_
intro a s _ ih
rw [Finset.sup_insert, Finset.sup_insert, sup_apply, ih]
section Restrict
variable [Zero β]
open scoped Classical in
/-- Restrict a simple function `f : α →ₛ β` to a set `s`. If `s` is measurable,
then `f.restrict s a = if a ∈ s then f a else 0`, otherwise `f.restrict s = const α 0`. -/
def restrict (f : α →ₛ β) (s : Set α) : α →ₛ β :=
if hs : MeasurableSet s then piecewise s hs f 0 else 0
theorem restrict_of_not_measurable {f : α →ₛ β} {s : Set α} (hs : ¬MeasurableSet s) :
restrict f s = 0 :=
dif_neg hs
@[simp]
theorem coe_restrict (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) :
⇑(restrict f s) = indicator s f := by
classical
rw [restrict, dif_pos hs, coe_piecewise, coe_zero, piecewise_eq_indicator]
@[simp]
theorem restrict_univ (f : α →ₛ β) : restrict f univ = f := by simp [restrict]
@[simp]
theorem restrict_empty (f : α →ₛ β) : restrict f ∅ = 0 := by simp [restrict]
open scoped Classical in
theorem map_restrict_of_zero [Zero γ] {g : β → γ} (hg : g 0 = 0) (f : α →ₛ β) (s : Set α) :
(f.restrict s).map g = (f.map g).restrict s :=
ext fun x =>
if hs : MeasurableSet s then by simp [hs, Set.indicator_comp_of_zero hg]
else by simp [restrict_of_not_measurable hs, hg]
theorem map_coe_ennreal_restrict (f : α →ₛ ℝ≥0) (s : Set α) :
(f.restrict s).map ((↑) : ℝ≥0 → ℝ≥0∞) = (f.map (↑)).restrict s :=
map_restrict_of_zero ENNReal.coe_zero _ _
theorem map_coe_nnreal_restrict (f : α →ₛ ℝ≥0) (s : Set α) :
(f.restrict s).map ((↑) : ℝ≥0 → ℝ) = (f.map (↑)).restrict s :=
map_restrict_of_zero NNReal.coe_zero _ _
theorem restrict_apply (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) (a) :
restrict f s a = indicator s f a := by simp only [f.coe_restrict hs]
theorem restrict_preimage (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) {t : Set β}
(ht : (0 : β) ∉ t) : restrict f s ⁻¹' t = s ∩ f ⁻¹' t := by
simp [hs, indicator_preimage_of_not_mem _ _ ht, inter_comm]
theorem restrict_preimage_singleton (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) {r : β}
(hr : r ≠ 0) : restrict f s ⁻¹' {r} = s ∩ f ⁻¹' {r} :=
f.restrict_preimage hs hr.symm
theorem mem_restrict_range {r : β} {s : Set α} {f : α →ₛ β} (hs : MeasurableSet s) :
r ∈ (restrict f s).range ↔ r = 0 ∧ s ≠ univ ∨ r ∈ f '' s := by
rw [← Finset.mem_coe, coe_range, coe_restrict _ hs, mem_range_indicator]
open scoped Classical in
theorem mem_image_of_mem_range_restrict {r : β} {s : Set α} {f : α →ₛ β}
(hr : r ∈ (restrict f s).range) (h0 : r ≠ 0) : r ∈ f '' s :=
if hs : MeasurableSet s then by simpa [mem_restrict_range hs, h0, -mem_range] using hr
else by
rw [restrict_of_not_measurable hs] at hr
exact (h0 <| eq_zero_of_mem_range_zero hr).elim
open scoped Classical in
@[gcongr, mono]
theorem restrict_mono [Preorder β] (s : Set α) {f g : α →ₛ β} (H : f ≤ g) :
f.restrict s ≤ g.restrict s :=
if hs : MeasurableSet s then fun x => by
simp only [coe_restrict _ hs, indicator_le_indicator (H x)]
else by simp only [restrict_of_not_measurable hs, le_refl]
end Restrict
section Approx
section
variable [SemilatticeSup β] [OrderBot β] [Zero β]
/-- Fix a sequence `i : ℕ → β`. Given a function `α → β`, its `n`-th approximation
by simple functions is defined so that in case `β = ℝ≥0∞` it sends each `a` to the supremum
of the set `{i k | k ≤ n ∧ i k ≤ f a}`, see `approx_apply` and `iSup_approx_apply` for details. -/
def approx (i : ℕ → β) (f : α → β) (n : ℕ) : α →ₛ β :=
(Finset.range n).sup fun k => restrict (const α (i k)) { a : α | i k ≤ f a }
open scoped Classical in
theorem approx_apply [TopologicalSpace β] [OrderClosedTopology β] [MeasurableSpace β]
[OpensMeasurableSpace β] {i : ℕ → β} {f : α → β} {n : ℕ} (a : α) (hf : Measurable f) :
(approx i f n : α →ₛ β) a = (Finset.range n).sup fun k => if i k ≤ f a then i k else 0 := by
dsimp only [approx]
rw [finset_sup_apply]
congr
funext k
rw [restrict_apply]
· simp only [coe_const, mem_setOf_eq, indicator_apply, Function.const_apply]
· exact hf measurableSet_Ici
theorem monotone_approx (i : ℕ → β) (f : α → β) : Monotone (approx i f) := fun _ _ h =>
Finset.sup_mono <| Finset.range_subset.2 h
theorem approx_comp [TopologicalSpace β] [OrderClosedTopology β] [MeasurableSpace β]
[OpensMeasurableSpace β] [MeasurableSpace γ] {i : ℕ → β} {f : γ → β} {g : α → γ} {n : ℕ} (a : α)
(hf : Measurable f) (hg : Measurable g) :
(approx i (f ∘ g) n : α →ₛ β) a = (approx i f n : γ →ₛ β) (g a) := by
rw [approx_apply _ hf, approx_apply _ (hf.comp hg), Function.comp_apply]
end
theorem iSup_approx_apply [TopologicalSpace β] [CompleteLattice β] [OrderClosedTopology β] [Zero β]
[MeasurableSpace β] [OpensMeasurableSpace β] (i : ℕ → β) (f : α → β) (a : α) (hf : Measurable f)
(h_zero : (0 : β) = ⊥) : ⨆ n, (approx i f n : α →ₛ β) a = ⨆ (k) (_ : i k ≤ f a), i k := by
refine le_antisymm (iSup_le fun n => ?_) (iSup_le fun k => iSup_le fun hk => ?_)
· rw [approx_apply a hf, h_zero]
refine Finset.sup_le fun k _ => ?_
split_ifs with h
· exact le_iSup_of_le k (le_iSup (fun _ : i k ≤ f a => i k) h)
· exact bot_le
· refine le_iSup_of_le (k + 1) ?_
rw [approx_apply a hf]
have : k ∈ Finset.range (k + 1) := Finset.mem_range.2 (Nat.lt_succ_self _)
refine le_trans (le_of_eq ?_) (Finset.le_sup this)
rw [if_pos hk]
end Approx
section EApprox
variable {f : α → ℝ≥0∞}
/-- A sequence of `ℝ≥0∞`s such that its range is the set of non-negative rational numbers. -/
def ennrealRatEmbed (n : ℕ) : ℝ≥0∞ :=
ENNReal.ofReal ((Encodable.decode (α := ℚ) n).getD (0 : ℚ))
theorem ennrealRatEmbed_encode (q : ℚ) :
ennrealRatEmbed (Encodable.encode q) = Real.toNNReal q := by
rw [ennrealRatEmbed, Encodable.encodek]; rfl
/-- Approximate a function `α → ℝ≥0∞` by a sequence of simple functions. -/
def eapprox : (α → ℝ≥0∞) → ℕ → α →ₛ ℝ≥0∞ :=
approx ennrealRatEmbed
theorem eapprox_lt_top (f : α → ℝ≥0∞) (n : ℕ) (a : α) : eapprox f n a < ∞ := by
simp only [eapprox, approx, finset_sup_apply, Finset.mem_range, ENNReal.bot_eq_zero, restrict]
rw [Finset.sup_lt_iff (α := ℝ≥0∞) WithTop.top_pos]
intro b _
split_ifs
· simp only [coe_zero, coe_piecewise, piecewise_eq_indicator, coe_const]
calc
{ a : α | ennrealRatEmbed b ≤ f a }.indicator (fun _ => ennrealRatEmbed b) a ≤
ennrealRatEmbed b :=
indicator_le_self _ _ a
_ < ⊤ := ENNReal.coe_lt_top
· exact WithTop.top_pos
@[mono]
theorem monotone_eapprox (f : α → ℝ≥0∞) : Monotone (eapprox f) :=
monotone_approx _ f
@[gcongr]
lemma eapprox_mono {m n : ℕ} (hmn : m ≤ n) : eapprox f m ≤ eapprox f n := monotone_eapprox _ hmn
lemma iSup_eapprox_apply (hf : Measurable f) (a : α) : ⨆ n, (eapprox f n : α →ₛ ℝ≥0∞) a = f a := by
rw [eapprox, iSup_approx_apply ennrealRatEmbed f a hf rfl]
refine le_antisymm (iSup_le fun i => iSup_le fun hi => hi) (le_of_not_gt ?_)
intro h
rcases ENNReal.lt_iff_exists_rat_btwn.1 h with ⟨q, _, lt_q, q_lt⟩
have :
(Real.toNNReal q : ℝ≥0∞) ≤ ⨆ (k : ℕ) (_ : ennrealRatEmbed k ≤ f a), ennrealRatEmbed k := by
refine le_iSup_of_le (Encodable.encode q) ?_
rw [ennrealRatEmbed_encode q]
exact le_iSup_of_le (le_of_lt q_lt) le_rfl
exact lt_irrefl _ (lt_of_le_of_lt this lt_q)
lemma iSup_coe_eapprox (hf : Measurable f) : ⨆ n, ⇑(eapprox f n) = f := by
simpa [funext_iff] using iSup_eapprox_apply hf
theorem eapprox_comp [MeasurableSpace γ] {f : γ → ℝ≥0∞} {g : α → γ} {n : ℕ} (hf : Measurable f)
(hg : Measurable g) : (eapprox (f ∘ g) n : α → ℝ≥0∞) = (eapprox f n : γ →ₛ ℝ≥0∞) ∘ g :=
funext fun a => approx_comp a hf hg
lemma tendsto_eapprox {f : α → ℝ≥0∞} (hf_meas : Measurable f) (a : α) :
Tendsto (fun n ↦ eapprox f n a) atTop (𝓝 (f a)) := by
nth_rw 2 [← iSup_coe_eapprox hf_meas]
rw [iSup_apply]
exact tendsto_atTop_iSup fun _ _ hnm ↦ monotone_eapprox f hnm a
/-- Approximate a function `α → ℝ≥0∞` by a series of simple functions taking their values
in `ℝ≥0`. -/
def eapproxDiff (f : α → ℝ≥0∞) : ℕ → α →ₛ ℝ≥0
| 0 => (eapprox f 0).map ENNReal.toNNReal
| n + 1 => (eapprox f (n + 1) - eapprox f n).map ENNReal.toNNReal
theorem sum_eapproxDiff (f : α → ℝ≥0∞) (n : ℕ) (a : α) :
(∑ k ∈ Finset.range (n + 1), (eapproxDiff f k a : ℝ≥0∞)) = eapprox f n a := by
induction' n with n IH
· simp only [Nat.zero_add, Finset.sum_singleton, Finset.range_one]
rfl
· rw [Finset.sum_range_succ, IH, eapproxDiff, coe_map, Function.comp_apply,
coe_sub, Pi.sub_apply, ENNReal.coe_toNNReal,
add_tsub_cancel_of_le (monotone_eapprox f (Nat.le_succ _) _)]
apply (lt_of_le_of_lt _ (eapprox_lt_top f (n + 1) a)).ne
rw [tsub_le_iff_right]
exact le_self_add
theorem tsum_eapproxDiff (f : α → ℝ≥0∞) (hf : Measurable f) (a : α) :
(∑' n, (eapproxDiff f n a : ℝ≥0∞)) = f a := by
simp_rw [ENNReal.tsum_eq_iSup_nat' (tendsto_add_atTop_nat 1), sum_eapproxDiff,
iSup_eapprox_apply hf a]
end EApprox
end Measurable
section Measure
variable {m : MeasurableSpace α} {μ ν : Measure α}
/-- Integral of a simple function whose codomain is `ℝ≥0∞`. -/
def lintegral {_m : MeasurableSpace α} (f : α →ₛ ℝ≥0∞) (μ : Measure α) : ℝ≥0∞ :=
∑ x ∈ f.range, x * μ (f ⁻¹' {x})
theorem lintegral_eq_of_subset (f : α →ₛ ℝ≥0∞) {s : Finset ℝ≥0∞}
(hs : ∀ x, f x ≠ 0 → μ (f ⁻¹' {f x}) ≠ 0 → f x ∈ s) :
f.lintegral μ = ∑ x ∈ s, x * μ (f ⁻¹' {x}) := by
refine Finset.sum_bij_ne_zero (fun r _ _ => r) ?_ ?_ ?_ ?_
· simpa only [forall_mem_range, mul_ne_zero_iff, and_imp]
· intros
assumption
· intro b _ hb
refine ⟨b, ?_, hb, rfl⟩
rw [mem_range, ← preimage_singleton_nonempty]
exact nonempty_of_measure_ne_zero (mul_ne_zero_iff.1 hb).2
· intros
rfl
theorem lintegral_eq_of_subset' (f : α →ₛ ℝ≥0∞) {s : Finset ℝ≥0∞} (hs : f.range \ {0} ⊆ s) :
f.lintegral μ = ∑ x ∈ s, x * μ (f ⁻¹' {x}) :=
f.lintegral_eq_of_subset fun x hfx _ =>
hs <| Finset.mem_sdiff.2 ⟨f.mem_range_self x, mt Finset.mem_singleton.1 hfx⟩
/-- Calculate the integral of `(g ∘ f)`, where `g : β → ℝ≥0∞` and `f : α →ₛ β`. -/
theorem map_lintegral (g : β → ℝ≥0∞) (f : α →ₛ β) :
(f.map g).lintegral μ = ∑ x ∈ f.range, g x * μ (f ⁻¹' {x}) := by
simp only [lintegral, range_map]
refine Finset.sum_image' _ fun b hb => ?_
rcases mem_range.1 hb with ⟨a, rfl⟩
rw [map_preimage_singleton, ← f.sum_measure_preimage_singleton, Finset.mul_sum]
refine Finset.sum_congr ?_ ?_
· congr
· intro x
simp only [Finset.mem_filter]
rintro ⟨_, h⟩
rw [h]
theorem add_lintegral (f g : α →ₛ ℝ≥0∞) : (f + g).lintegral μ = f.lintegral μ + g.lintegral μ :=
calc
(f + g).lintegral μ =
∑ x ∈ (pair f g).range, (x.1 * μ (pair f g ⁻¹' {x}) + x.2 * μ (pair f g ⁻¹' {x})) := by
rw [add_eq_map₂, map_lintegral]; exact Finset.sum_congr rfl fun a _ => add_mul _ _ _
_ = (∑ x ∈ (pair f g).range, x.1 * μ (pair f g ⁻¹' {x})) +
∑ x ∈ (pair f g).range, x.2 * μ (pair f g ⁻¹' {x}) := by
rw [Finset.sum_add_distrib]
_ = ((pair f g).map Prod.fst).lintegral μ + ((pair f g).map Prod.snd).lintegral μ := by
rw [map_lintegral, map_lintegral]
_ = lintegral f μ + lintegral g μ := rfl
theorem const_mul_lintegral (f : α →ₛ ℝ≥0∞) (x : ℝ≥0∞) :
(const α x * f).lintegral μ = x * f.lintegral μ :=
calc
(f.map fun a => x * a).lintegral μ = ∑ r ∈ f.range, x * r * μ (f ⁻¹' {r}) := map_lintegral _ _
_ = x * ∑ r ∈ f.range, r * μ (f ⁻¹' {r}) := by simp_rw [Finset.mul_sum, mul_assoc]
/-- Integral of a simple function `α →ₛ ℝ≥0∞` as a bilinear map. -/
def lintegralₗ {m : MeasurableSpace α} : (α →ₛ ℝ≥0∞) →ₗ[ℝ≥0∞] Measure α →ₗ[ℝ≥0∞] ℝ≥0∞ where
toFun f :=
{ toFun := lintegral f
map_add' := by simp [lintegral, mul_add, Finset.sum_add_distrib]
map_smul' := fun c μ => by
simp [lintegral, mul_left_comm _ c, Finset.mul_sum, Measure.smul_apply c] }
map_add' f g := LinearMap.ext fun _ => add_lintegral f g
map_smul' c f := LinearMap.ext fun _ => const_mul_lintegral f c
@[simp]
theorem zero_lintegral : (0 : α →ₛ ℝ≥0∞).lintegral μ = 0 :=
LinearMap.ext_iff.1 lintegralₗ.map_zero μ
theorem lintegral_add {ν} (f : α →ₛ ℝ≥0∞) : f.lintegral (μ + ν) = f.lintegral μ + f.lintegral ν :=
(lintegralₗ f).map_add μ ν
theorem lintegral_smul {R : Type*} [SMul R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞]
(f : α →ₛ ℝ≥0∞) (c : R) : f.lintegral (c • μ) = c • f.lintegral μ := by
simpa only [smul_one_smul] using (lintegralₗ f).map_smul (c • 1) μ
@[simp]
theorem lintegral_zero [MeasurableSpace α] (f : α →ₛ ℝ≥0∞) : f.lintegral 0 = 0 :=
(lintegralₗ f).map_zero
theorem lintegral_finset_sum {ι} (f : α →ₛ ℝ≥0∞) (μ : ι → Measure α) (s : Finset ι) :
f.lintegral (∑ i ∈ s, μ i) = ∑ i ∈ s, f.lintegral (μ i) :=
map_sum (lintegralₗ f) ..
theorem lintegral_sum {m : MeasurableSpace α} {ι} (f : α →ₛ ℝ≥0∞) (μ : ι → Measure α) :
f.lintegral (Measure.sum μ) = ∑' i, f.lintegral (μ i) := by
simp only [lintegral, Measure.sum_apply, f.measurableSet_preimage, ← Finset.tsum_subtype, ←
ENNReal.tsum_mul_left]
apply ENNReal.tsum_comm
open scoped Classical in
theorem restrict_lintegral (f : α →ₛ ℝ≥0∞) {s : Set α} (hs : MeasurableSet s) :
(restrict f s).lintegral μ = ∑ r ∈ f.range, r * μ (f ⁻¹' {r} ∩ s) :=
calc
(restrict f s).lintegral μ = ∑ r ∈ f.range, r * μ (restrict f s ⁻¹' {r}) :=
lintegral_eq_of_subset _ fun x hx =>
if hxs : x ∈ s then fun _ => by
simp only [f.restrict_apply hs, indicator_of_mem hxs, mem_range_self]
else False.elim <| hx <| by simp [*]
_ = ∑ r ∈ f.range, r * μ (f ⁻¹' {r} ∩ s) :=
Finset.sum_congr rfl <|
forall_mem_range.2 fun b =>
if hb : f b = 0 then by simp only [hb, zero_mul]
else by rw [restrict_preimage_singleton _ hs hb, inter_comm]
theorem lintegral_restrict {m : MeasurableSpace α} (f : α →ₛ ℝ≥0∞) (s : Set α) (μ : Measure α) :
f.lintegral (μ.restrict s) = ∑ y ∈ f.range, y * μ (f ⁻¹' {y} ∩ s) := by
simp only [lintegral, Measure.restrict_apply, f.measurableSet_preimage]
theorem restrict_lintegral_eq_lintegral_restrict (f : α →ₛ ℝ≥0∞) {s : Set α}
(hs : MeasurableSet s) : (restrict f s).lintegral μ = f.lintegral (μ.restrict s) := by
rw [f.restrict_lintegral hs, lintegral_restrict]
theorem lintegral_restrict_iUnion_of_directed {ι : Type*} [Countable ι]
(f : α →ₛ ℝ≥0∞) {s : ι → Set α} (hd : Directed (· ⊆ ·) s) (μ : Measure α) :
f.lintegral (μ.restrict (⋃ i, s i)) = ⨆ i, f.lintegral (μ.restrict (s i)) := by
simp only [lintegral, Measure.restrict_iUnion_apply_eq_iSup hd (measurableSet_preimage ..),
ENNReal.mul_iSup]
refine finsetSum_iSup fun i j ↦ (hd i j).imp fun k ⟨hik, hjk⟩ ↦ fun a ↦ ?_
-- TODO https://github.com/leanprover-community/mathlib4/pull/14739 make `gcongr` close this goal
constructor <;> · gcongr; refine Measure.restrict_mono ?_ le_rfl _; assumption
theorem const_lintegral (c : ℝ≥0∞) : (const α c).lintegral μ = c * μ univ := by
rw [lintegral]
cases isEmpty_or_nonempty α
· simp [μ.eq_zero_of_isEmpty]
· simp only [range_const, coe_const, Finset.sum_singleton]
unfold Function.const; rw [preimage_const_of_mem (mem_singleton c)]
theorem const_lintegral_restrict (c : ℝ≥0∞) (s : Set α) :
(const α c).lintegral (μ.restrict s) = c * μ s := by
rw [const_lintegral, Measure.restrict_apply MeasurableSet.univ, univ_inter]
theorem restrict_const_lintegral (c : ℝ≥0∞) {s : Set α} (hs : MeasurableSet s) :
((const α c).restrict s).lintegral μ = c * μ s := by
rw [restrict_lintegral_eq_lintegral_restrict _ hs, const_lintegral_restrict]
@[gcongr]
theorem lintegral_mono_fun {f g : α →ₛ ℝ≥0∞} (h : f ≤ g) : f.lintegral μ ≤ g.lintegral μ := by
refine Monotone.of_left_le_map_sup (f := (lintegral · μ)) (fun f g ↦ ?_) h
calc
f.lintegral μ = ((pair f g).map Prod.fst).lintegral μ := by rw [map_fst_pair]
_ ≤ ((pair f g).map fun p ↦ p.1 ⊔ p.2).lintegral μ := by
simp only [map_lintegral]
gcongr
exact le_sup_left
theorem le_sup_lintegral (f g : α →ₛ ℝ≥0∞) : f.lintegral μ ⊔ g.lintegral μ ≤ (f ⊔ g).lintegral μ :=
Monotone.le_map_sup (fun _ _ ↦ lintegral_mono_fun) f g
@[gcongr]
| Mathlib/MeasureTheory/Function/SimpleFunc.lean | 991 | 1,002 | theorem lintegral_mono_measure {f : α →ₛ ℝ≥0∞} (h : μ ≤ ν) : f.lintegral μ ≤ f.lintegral ν := by | simp only [lintegral]
gcongr
apply h
/-- `SimpleFunc.lintegral` is monotone both in function and in measure. -/
@[mono, gcongr]
theorem lintegral_mono {f g : α →ₛ ℝ≥0∞} (hfg : f ≤ g) (hμν : μ ≤ ν) :
f.lintegral μ ≤ g.lintegral ν :=
(lintegral_mono_fun hfg).trans (lintegral_mono_measure hμν)
/-- `SimpleFunc.lintegral` depends only on the measures of `f ⁻¹' {y}`. -/ |
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Kim Morrison
-/
import Mathlib.Tactic.NormNum.Basic
import Mathlib.Tactic.TryThis
import Mathlib.Util.AtomM
/-!
# The `abel` tactic
Evaluate expressions in the language of additive, commutative monoids and groups.
-/
-- TODO: assert_not_exists NonUnitalNonAssociativeSemiring
assert_not_exists OrderedAddCommMonoid TopologicalSpace PseudoMetricSpace
namespace Mathlib.Tactic.Abel
open Lean Elab Meta Tactic Qq
initialize registerTraceClass `abel
initialize registerTraceClass `abel.detail
/--
Tactic for evaluating equations in the language of
*additive*, commutative monoids and groups.
`abel` and its variants work as both tactics and conv tactics.
* `abel1` fails if the target is not an equality that is provable by the axioms of
commutative monoids/groups.
* `abel_nf` rewrites all group expressions into a normal form.
* In tactic mode, `abel_nf at h` can be used to rewrite in a hypothesis.
* `abel_nf (config := cfg)` allows for additional configuration:
* `red`: the reducibility setting (overridden by `!`)
* `zetaDelta`: if true, local let variables can be unfolded (overridden by `!`)
* `recursive`: if true, `abel_nf` will also recurse into atoms
* `abel!`, `abel1!`, `abel_nf!` will use a more aggressive reducibility setting to identify atoms.
For example:
```
example [AddCommMonoid α] (a b : α) : a + (b + a) = a + a + b := by abel
example [AddCommGroup α] (a : α) : (3 : ℤ) • a = a + (2 : ℤ) • a := by abel
```
## Future work
* In mathlib 3, `abel` accepted additional optional arguments:
```
syntax "abel" (&" raw" <|> &" term")? (location)? : tactic
```
It is undecided whether these features should be restored eventually.
-/
syntax (name := abel) "abel" "!"? : tactic
/-- The `Context` for a call to `abel`.
Stores a few options for this call, and caches some common subexpressions
such as typeclass instances and `0 : α`.
-/
structure Context where
/-- The type of the ambient additive commutative group or monoid. -/
α : Expr
/-- The universe level for `α`. -/
univ : Level
/-- The expression representing `0 : α`. -/
α0 : Expr
/-- Specify whether we are in an additive commutative group or an additive commutative monoid. -/
isGroup : Bool
/-- The `AddCommGroup α` or `AddCommMonoid α` expression. -/
inst : Expr
/-- Populate a `context` object for evaluating `e`. -/
def mkContext (e : Expr) : MetaM Context := do
let α ← inferType e
let c ← synthInstance (← mkAppM ``AddCommMonoid #[α])
let cg ← synthInstance? (← mkAppM ``AddCommGroup #[α])
let u ← mkFreshLevelMVar
_ ← isDefEq (.sort (.succ u)) (← inferType α)
let α0 ← Expr.ofNat α 0
match cg with
| some cg => return ⟨α, u, α0, true, cg⟩
| _ => return ⟨α, u, α0, false, c⟩
/-- The monad for `Abel` contains, in addition to the `AtomM` state,
some information about the current type we are working over, so that we can consistently
use group lemmas or monoid lemmas as appropriate. -/
abbrev M := ReaderT Context AtomM
/-- Apply the function `n : ∀ {α} [inst : AddWhatever α], _` to the
implicit parameters in the context, and the given list of arguments. -/
def Context.app (c : Context) (n : Name) (inst : Expr) : Array Expr → Expr :=
mkAppN (((@Expr.const n [c.univ]).app c.α).app inst)
/-- Apply the function `n : ∀ {α} [inst α], _` to the implicit parameters in the
context, and the given list of arguments.
Compared to `context.app`, this takes the name of the typeclass, rather than an
inferred typeclass instance.
-/
def Context.mkApp (c : Context) (n inst : Name) (l : Array Expr) : MetaM Expr := do
return c.app n (← synthInstance ((Expr.const inst [c.univ]).app c.α)) l
/-- Add the letter "g" to the end of the name, e.g. turning `term` into `termg`.
This is used to choose between declarations taking `AddCommMonoid` and those
taking `AddCommGroup` instances.
-/
def addG : Name → Name
| .str p s => .str p (s ++ "g")
| n => n
/-- Apply the function `n : ∀ {α} [AddComm{Monoid,Group} α]` to the given list of arguments.
Will use the `AddComm{Monoid,Group}` instance that has been cached in the context.
-/
def iapp (n : Name) (xs : Array Expr) : M Expr := do
let c ← read
return c.app (if c.isGroup then addG n else n) c.inst xs
/-- A type synonym used by `abel` to represent `n • x + a` in an additive commutative monoid. -/
def term {α} [AddCommMonoid α] (n : ℕ) (x a : α) : α := n • x + a
/-- A type synonym used by `abel` to represent `n • x + a` in an additive commutative group. -/
def termg {α} [AddCommGroup α] (n : ℤ) (x a : α) : α := n • x + a
/-- Evaluate a term with coefficient `n`, atom `x` and successor terms `a`. -/
def mkTerm (n x a : Expr) : M Expr := iapp ``term #[n, x, a]
/-- Interpret an integer as a coefficient to a term. -/
def intToExpr (n : ℤ) : M Expr := do
Expr.ofInt (mkConst (if (← read).isGroup then ``Int else ``Nat) []) n
/-- A normal form for `abel`.
Expressions are represented as a list of terms of the form `e = n • x`,
where `n : ℤ` and `x` is an arbitrary element of the additive commutative monoid or group.
We explicitly track the `Expr` forms of `e` and `n`, even though they could be reconstructed,
for efficiency. -/
inductive NormalExpr : Type
| zero (e : Expr) : NormalExpr
| nterm (e : Expr) (n : Expr × ℤ) (x : ℕ × Expr) (a : NormalExpr) : NormalExpr
deriving Inhabited
/-- Extract the expression from a normal form. -/
def NormalExpr.e : NormalExpr → Expr
| .zero e => e
| .nterm e .. => e
instance : Coe NormalExpr Expr where coe := NormalExpr.e
/-- Construct the normal form representing a single term. -/
def NormalExpr.term' (n : Expr × ℤ) (x : ℕ × Expr) (a : NormalExpr) : M NormalExpr :=
return .nterm (← mkTerm n.1 x.2 a) n x a
/-- Construct the normal form representing zero. -/
def NormalExpr.zero' : M NormalExpr := return NormalExpr.zero (← read).α0
open NormalExpr
| Mathlib/Tactic/Abel.lean | 162 | 163 | theorem const_add_term {α} [AddCommMonoid α] (k n x a a') (h : k + a = a') :
k + @term α _ n x a = term n x a' := by | |
/-
Copyright (c) 2023 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Dynamics.BirkhoffSum.Basic
import Mathlib.Algebra.Module.Basic
/-!
# Birkhoff average
In this file we define `birkhoffAverage f g n x` to be
$$
\frac{1}{n}\sum_{k=0}^{n-1}g(f^{[k]}(x)),
$$
where `f : α → α` is a self-map on some type `α`,
`g : α → M` is a function from `α` to a module over a division semiring `R`,
and `R` is used to formalize division by `n` as `(n : R)⁻¹ • _`.
While we need an auxiliary division semiring `R` to define `birkhoffAverage`,
the definition does not depend on the choice of `R`,
see `birkhoffAverage_congr_ring`.
-/
open Finset
section birkhoffAverage
variable (R : Type*) {α M : Type*} [DivisionSemiring R] [AddCommMonoid M] [Module R M]
/-- The average value of `g` on the first `n` points of the orbit of `x` under `f`,
i.e. the Birkhoff sum `∑ k ∈ Finset.range n, g (f^[k] x)` divided by `n`.
This average appears in many ergodic theorems
which say that `(birkhoffAverage R f g · x)`
converges to the "space average" `⨍ x, g x ∂μ` as `n → ∞`.
We use an auxiliary `[DivisionSemiring R]` to define division by `n`.
However, the definition does not depend on the choice of `R`,
see `birkhoffAverage_congr_ring`. -/
def birkhoffAverage (f : α → α) (g : α → M) (n : ℕ) (x : α) : M := (n : R)⁻¹ • birkhoffSum f g n x
| Mathlib/Dynamics/BirkhoffSum/Average.lean | 44 | 45 | theorem birkhoffAverage_zero (f : α → α) (g : α → M) (x : α) :
birkhoffAverage R f g 0 x = 0 := by | simp [birkhoffAverage] |
/-
Copyright (c) 2020 Aaron Anderson, Jalex Stark. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Jalex Stark
-/
import Mathlib.Algebra.Polynomial.Expand
import Mathlib.Algebra.Polynomial.Laurent
import Mathlib.Algebra.Polynomial.Eval.SMul
import Mathlib.LinearAlgebra.Matrix.Charpoly.Basic
import Mathlib.LinearAlgebra.Matrix.Reindex
import Mathlib.RingTheory.Polynomial.Nilpotent
/-!
# Characteristic polynomials
We give methods for computing coefficients of the characteristic polynomial.
## Main definitions
- `Matrix.charpoly_degree_eq_dim` proves that the degree of the characteristic polynomial
over a nonzero ring is the dimension of the matrix
- `Matrix.det_eq_sign_charpoly_coeff` proves that the determinant is the constant term of the
characteristic polynomial, up to sign.
- `Matrix.trace_eq_neg_charpoly_coeff` proves that the trace is the negative of the (d-1)th
coefficient of the characteristic polynomial, where d is the dimension of the matrix.
For a nonzero ring, this is the second-highest coefficient.
- `Matrix.charpolyRev` the reverse of the characteristic polynomial.
- `Matrix.reverse_charpoly` characterises the reverse of the characteristic polynomial.
-/
noncomputable section
universe u v w z
open Finset Matrix Polynomial
variable {R : Type u} [CommRing R]
variable {n G : Type v} [DecidableEq n] [Fintype n]
variable {α β : Type v} [DecidableEq α]
variable {M : Matrix n n R}
namespace Matrix
theorem charmatrix_apply_natDegree [Nontrivial R] (i j : n) :
(charmatrix M i j).natDegree = ite (i = j) 1 0 := by
by_cases h : i = j <;> simp [h, ← degree_eq_iff_natDegree_eq_of_pos (Nat.succ_pos 0)]
theorem charmatrix_apply_natDegree_le (i j : n) :
(charmatrix M i j).natDegree ≤ ite (i = j) 1 0 := by
split_ifs with h <;> simp [h, natDegree_X_le]
variable (M)
theorem charpoly_sub_diagonal_degree_lt :
(M.charpoly - ∏ i : n, (X - C (M i i))).degree < ↑(Fintype.card n - 1) := by
rw [charpoly, det_apply', ← insert_erase (mem_univ (Equiv.refl n)),
sum_insert (not_mem_erase (Equiv.refl n) univ), add_comm]
simp only [charmatrix_apply_eq, one_mul, Equiv.Perm.sign_refl, id, Int.cast_one,
Units.val_one, add_sub_cancel_right, Equiv.coe_refl]
rw [← mem_degreeLT]
apply Submodule.sum_mem (degreeLT R (Fintype.card n - 1))
intro c hc; rw [← C_eq_intCast, C_mul']
apply Submodule.smul_mem (degreeLT R (Fintype.card n - 1)) ↑↑(Equiv.Perm.sign c)
rw [mem_degreeLT]
apply lt_of_le_of_lt degree_le_natDegree _
rw [Nat.cast_lt]
apply lt_of_le_of_lt _ (Equiv.Perm.fixed_point_card_lt_of_ne_one (ne_of_mem_erase hc))
apply le_trans (Polynomial.natDegree_prod_le univ fun i : n => charmatrix M (c i) i) _
rw [card_eq_sum_ones]; rw [sum_filter]; apply sum_le_sum
intros
apply charmatrix_apply_natDegree_le
theorem charpoly_coeff_eq_prod_coeff_of_le {k : ℕ} (h : Fintype.card n - 1 ≤ k) :
M.charpoly.coeff k = (∏ i : n, (X - C (M i i))).coeff k := by
apply eq_of_sub_eq_zero; rw [← coeff_sub]
apply Polynomial.coeff_eq_zero_of_degree_lt
apply lt_of_lt_of_le (charpoly_sub_diagonal_degree_lt M) ?_
rw [Nat.cast_le]; apply h
theorem det_of_card_zero (h : Fintype.card n = 0) (M : Matrix n n R) : M.det = 1 := by
rw [Fintype.card_eq_zero_iff] at h
suffices M = 1 by simp [this]
ext i
exact h.elim i
theorem charpoly_degree_eq_dim [Nontrivial R] (M : Matrix n n R) :
M.charpoly.degree = Fintype.card n := by
by_cases h : Fintype.card n = 0
· rw [h]
unfold charpoly
rw [det_of_card_zero]
· simp
· assumption
rw [← sub_add_cancel M.charpoly (∏ i : n, (X - C (M i i)))]
-- Porting note: added `↑` in front of `Fintype.card n`
have h1 : (∏ i : n, (X - C (M i i))).degree = ↑(Fintype.card n) := by
rw [degree_eq_iff_natDegree_eq_of_pos (Nat.pos_of_ne_zero h), natDegree_prod']
· simp_rw [natDegree_X_sub_C]
rw [← Finset.card_univ, sum_const, smul_eq_mul, mul_one]
simp_rw [(monic_X_sub_C _).leadingCoeff]
simp
rw [degree_add_eq_right_of_degree_lt]
· exact h1
rw [h1]
apply lt_trans (charpoly_sub_diagonal_degree_lt M)
rw [Nat.cast_lt]
rw [← Nat.pred_eq_sub_one]
apply Nat.pred_lt
apply h
@[simp] theorem charpoly_natDegree_eq_dim [Nontrivial R] (M : Matrix n n R) :
M.charpoly.natDegree = Fintype.card n :=
natDegree_eq_of_degree_eq_some (charpoly_degree_eq_dim M)
theorem charpoly_monic (M : Matrix n n R) : M.charpoly.Monic := by
nontriviality R
by_cases h : Fintype.card n = 0
· rw [charpoly, det_of_card_zero h]
apply monic_one
have mon : (∏ i : n, (X - C (M i i))).Monic := by
apply monic_prod_of_monic univ fun i : n => X - C (M i i)
simp [monic_X_sub_C]
rw [← sub_add_cancel (∏ i : n, (X - C (M i i))) M.charpoly] at mon
rw [Monic] at *
rwa [leadingCoeff_add_of_degree_lt] at mon
rw [charpoly_degree_eq_dim]
rw [← neg_sub]
rw [degree_neg]
apply lt_trans (charpoly_sub_diagonal_degree_lt M)
rw [Nat.cast_lt]
rw [← Nat.pred_eq_sub_one]
apply Nat.pred_lt
apply h
/-- See also `Matrix.coeff_charpolyRev_eq_neg_trace`. -/
theorem trace_eq_neg_charpoly_coeff [Nonempty n] (M : Matrix n n R) :
trace M = -M.charpoly.coeff (Fintype.card n - 1) := by
rw [charpoly_coeff_eq_prod_coeff_of_le _ le_rfl, Fintype.card,
prod_X_sub_C_coeff_card_pred univ (fun i : n => M i i) Fintype.card_pos, neg_neg, trace]
simp_rw [diag_apply]
theorem matPolyEquiv_symm_map_eval (M : (Matrix n n R)[X]) (r : R) :
(matPolyEquiv.symm M).map (eval r) = M.eval (scalar n r) := by
suffices ((aeval r).mapMatrix.comp matPolyEquiv.symm.toAlgHom : (Matrix n n R)[X] →ₐ[R] _) =
(eval₂AlgHom' (AlgHom.id R _) (scalar n r)
fun x => (scalar_commute _ (Commute.all _) _).symm) from
DFunLike.congr_fun this M
ext : 1
· ext M : 1
simp [Function.comp_def]
· simp [smul_eq_diagonal_mul]
theorem matPolyEquiv_eval_eq_map (M : Matrix n n R[X]) (r : R) :
(matPolyEquiv M).eval (scalar n r) = M.map (eval r) := by
simpa only [AlgEquiv.symm_apply_apply] using (matPolyEquiv_symm_map_eval (matPolyEquiv M) r).symm
-- I feel like this should use `Polynomial.algHom_eval₂_algebraMap`
theorem matPolyEquiv_eval (M : Matrix n n R[X]) (r : R) (i j : n) :
(matPolyEquiv M).eval (scalar n r) i j = (M i j).eval r := by
rw [matPolyEquiv_eval_eq_map, map_apply]
theorem eval_det (M : Matrix n n R[X]) (r : R) :
Polynomial.eval r M.det = (Polynomial.eval (scalar n r) (matPolyEquiv M)).det := by
rw [Polynomial.eval, ← coe_eval₂RingHom, RingHom.map_det]
apply congr_arg det
ext
symm
exact matPolyEquiv_eval _ _ _ _
| Mathlib/LinearAlgebra/Matrix/Charpoly/Coeff.lean | 172 | 174 | theorem det_eq_sign_charpoly_coeff (M : Matrix n n R) :
M.det = (-1) ^ Fintype.card n * M.charpoly.coeff 0 := by | rw [coeff_zero_eq_eval_zero, charpoly, eval_det, matPolyEquiv_charmatrix, ← det_smul] |
/-
Copyright (c) 2020 Anatole Dedecker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker
-/
import Mathlib.Algebra.Order.Floor.Ring
import Mathlib.Order.Filter.AtTopBot.Floor
import Mathlib.Topology.Algebra.Order.Group
/-!
# Topological facts about `Int.floor`, `Int.ceil` and `Int.fract`
This file proves statements about limits and continuity of functions involving `floor`, `ceil` and
`fract`.
## Main declarations
* `tendsto_floor_atTop`, `tendsto_floor_atBot`, `tendsto_ceil_atTop`, `tendsto_ceil_atBot`:
`Int.floor` and `Int.ceil` tend to +-∞ in +-∞.
* `continuousOn_floor`: `Int.floor` is continuous on `Ico n (n + 1)`, because constant.
* `continuousOn_ceil`: `Int.ceil` is continuous on `Ioc n (n + 1)`, because constant.
* `continuousOn_fract`: `Int.fract` is continuous on `Ico n (n + 1)`.
* `ContinuousOn.comp_fract`: Precomposing a continuous function satisfying `f 0 = f 1` with
`Int.fract` yields another continuous function.
-/
open Filter Function Int Set Topology
namespace FloorSemiring
open scoped Nat
variable {K : Type*} [Field K] [LinearOrder K] [IsStrictOrderedRing K] [FloorSemiring K]
[TopologicalSpace K] [OrderTopology K]
theorem tendsto_mul_pow_div_factorial_sub_atTop (a c : K) (d : ℕ) :
Tendsto (fun n ↦ a * c ^ n / (n - d)!) atTop (𝓝 0) := by
rw [tendsto_order]
constructor
all_goals
intro ε hε
filter_upwards [eventually_mul_pow_lt_factorial_sub (a * ε⁻¹) c d] with n h
rw [mul_right_comm, ← div_eq_mul_inv] at h
· rw [div_lt_iff_of_neg hε] at h
rwa [lt_div_iff₀' (Nat.cast_pos.mpr (Nat.factorial_pos _))]
· rw [div_lt_iff₀ hε] at h
rwa [div_lt_iff₀' (Nat.cast_pos.mpr (Nat.factorial_pos _))]
theorem tendsto_pow_div_factorial_atTop (c : K) :
Tendsto (fun n ↦ c ^ n / n !) atTop (𝓝 0) := by
convert tendsto_mul_pow_div_factorial_sub_atTop 1 c 0
rw [one_mul]
end FloorSemiring
variable {α β γ : Type*} [Ring α] [LinearOrder α] [FloorRing α]
section
variable [IsStrictOrderedRing α]
-- TODO: move to `Mathlib.Order.Filter.AtTopBot.Floor`
theorem tendsto_floor_atTop : Tendsto (floor : α → ℤ) atTop atTop :=
floor_mono.tendsto_atTop_atTop fun b =>
⟨(b + 1 : ℤ), by rw [floor_intCast]; exact (lt_add_one _).le⟩
theorem tendsto_floor_atBot : Tendsto (floor : α → ℤ) atBot atBot :=
floor_mono.tendsto_atBot_atBot fun b => ⟨b, (floor_intCast _).le⟩
theorem tendsto_ceil_atTop : Tendsto (ceil : α → ℤ) atTop atTop :=
ceil_mono.tendsto_atTop_atTop fun b => ⟨b, (ceil_intCast _).ge⟩
theorem tendsto_ceil_atBot : Tendsto (ceil : α → ℤ) atBot atBot :=
ceil_mono.tendsto_atBot_atBot fun b =>
⟨(b - 1 : ℤ), by rw [ceil_intCast]; exact (sub_one_lt _).le⟩
end
variable [TopologicalSpace α]
theorem continuousOn_floor (n : ℤ) :
ContinuousOn (fun x => floor x : α → α) (Ico n (n + 1) : Set α) :=
(continuousOn_congr <| floor_eq_on_Ico' n).mpr continuousOn_const
theorem continuousOn_ceil [IsStrictOrderedRing α] (n : ℤ) :
ContinuousOn (fun x => ceil x : α → α) (Ioc (n - 1) n : Set α) :=
(continuousOn_congr <| ceil_eq_on_Ioc' n).mpr continuousOn_const
section OrderClosedTopology
variable [IsStrictOrderedRing α] [OrderClosedTopology α]
omit [IsStrictOrderedRing α] in
| Mathlib/Topology/Algebra/Order/Floor.lean | 94 | 98 | theorem tendsto_floor_right_pure_floor (x : α) : Tendsto (floor : α → ℤ) (𝓝[≥] x) (pure ⌊x⌋) :=
tendsto_pure.2 <| mem_of_superset (Ico_mem_nhdsGE <| lt_floor_add_one x) fun _y hy =>
floor_eq_on_Ico _ _ ⟨(floor_le x).trans hy.1, hy.2⟩
theorem tendsto_floor_right_pure (n : ℤ) : Tendsto (floor : α → ℤ) (𝓝[≥] n) (pure n) := by | |
/-
Copyright (c) 2022 Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kyle Miller, Vincent Beffara, Rida Hamadani
-/
import Mathlib.Combinatorics.SimpleGraph.Path
import Mathlib.Data.ENat.Lattice
/-!
# Graph metric
This module defines the `SimpleGraph.edist` function, which takes pairs of vertices to the length of
the shortest walk between them, or `⊤` if they are disconnected. It also defines `SimpleGraph.dist`
which is the `ℕ`-valued version of `SimpleGraph.edist`.
## Main definitions
- `SimpleGraph.edist` is the graph extended metric.
- `SimpleGraph.dist` is the graph metric.
## TODO
- Provide an additional computable version of `SimpleGraph.dist`
for when `G` is connected.
- When directed graphs exist, a directed notion of distance,
likely `ENat`-valued.
## Tags
graph metric, distance
-/
assert_not_exists Field
namespace SimpleGraph
variable {V : Type*} (G : SimpleGraph V)
/-! ## Metric -/
section edist
/--
The extended distance between two vertices is the length of the shortest walk between them.
It is `⊤` if no such walk exists.
-/
noncomputable def edist (u v : V) : ℕ∞ :=
⨅ w : G.Walk u v, w.length
variable {G} {u v w : V}
theorem edist_eq_sInf : G.edist u v = sInf (Set.range fun w : G.Walk u v ↦ (w.length : ℕ∞)) := rfl
protected theorem Reachable.exists_walk_length_eq_edist (hr : G.Reachable u v) :
∃ p : G.Walk u v, p.length = G.edist u v :=
csInf_mem <| Set.range_nonempty_iff_nonempty.mpr hr
protected theorem Connected.exists_walk_length_eq_edist (hconn : G.Connected) (u v : V) :
∃ p : G.Walk u v, p.length = G.edist u v :=
(hconn u v).exists_walk_length_eq_edist
theorem edist_le (p : G.Walk u v) :
G.edist u v ≤ p.length :=
sInf_le ⟨p, rfl⟩
protected alias Walk.edist_le := edist_le
@[simp]
| Mathlib/Combinatorics/SimpleGraph/Metric.lean | 70 | 71 | theorem edist_eq_zero_iff :
G.edist u v = 0 ↔ u = v := by | |
/-
Copyright (c) 2021 Thomas Browning. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Thomas Browning
-/
import Mathlib.Algebra.BigOperators.GroupWithZero.Finset
import Mathlib.Algebra.GroupWithZero.Subgroup
import Mathlib.Data.Finite.Card
import Mathlib.Data.Finite.Prod
import Mathlib.Data.Set.Card
import Mathlib.GroupTheory.Coset.Card
import Mathlib.GroupTheory.GroupAction.Quotient
import Mathlib.GroupTheory.QuotientGroup.Basic
/-!
# Index of a Subgroup
In this file we define the index of a subgroup, and prove several divisibility properties.
Several theorems proved in this file are known as Lagrange's theorem.
## Main definitions
- `H.index` : the index of `H : Subgroup G` as a natural number,
and returns 0 if the index is infinite.
- `H.relindex K` : the relative index of `H : Subgroup G` in `K : Subgroup G` as a natural number,
and returns 0 if the relative index is infinite.
# Main results
- `card_mul_index` : `Nat.card H * H.index = Nat.card G`
- `index_mul_card` : `H.index * Fintype.card H = Fintype.card G`
- `index_dvd_card` : `H.index ∣ Fintype.card G`
- `relindex_mul_index` : If `H ≤ K`, then `H.relindex K * K.index = H.index`
- `index_dvd_of_le` : If `H ≤ K`, then `K.index ∣ H.index`
- `relindex_mul_relindex` : `relindex` is multiplicative in towers
- `MulAction.index_stabilizer`: the index of the stabilizer is the cardinality of the orbit
-/
assert_not_exists Field
open scoped Pointwise
namespace Subgroup
open Cardinal Function
variable {G G' : Type*} [Group G] [Group G'] (H K L : Subgroup G)
/-- The index of a subgroup as a natural number. Returns `0` if the index is infinite. -/
@[to_additive "The index of an additive subgroup as a natural number.
Returns 0 if the index is infinite."]
noncomputable def index : ℕ :=
Nat.card (G ⧸ H)
/-- If `H` and `K` are subgroups of a group `G`, then `relindex H K : ℕ` is the index
of `H ∩ K` in `K`. The function returns `0` if the index is infinite. -/
@[to_additive "If `H` and `K` are subgroups of an additive group `G`, then `relindex H K : ℕ`
is the index of `H ∩ K` in `K`. The function returns `0` if the index is infinite."]
noncomputable def relindex : ℕ :=
(H.subgroupOf K).index
@[to_additive]
theorem index_comap_of_surjective {f : G' →* G} (hf : Function.Surjective f) :
(H.comap f).index = H.index := by
have key : ∀ x y : G',
QuotientGroup.leftRel (H.comap f) x y ↔ QuotientGroup.leftRel H (f x) (f y) := by
simp only [QuotientGroup.leftRel_apply]
exact fun x y => iff_of_eq (congr_arg (· ∈ H) (by rw [f.map_mul, f.map_inv]))
refine Cardinal.toNat_congr (Equiv.ofBijective (Quotient.map' f fun x y => (key x y).mp) ⟨?_, ?_⟩)
· simp_rw [← Quotient.eq''] at key
refine Quotient.ind' fun x => ?_
refine Quotient.ind' fun y => ?_
exact (key x y).mpr
· refine Quotient.ind' fun x => ?_
obtain ⟨y, hy⟩ := hf x
exact ⟨y, (Quotient.map'_mk'' f _ y).trans (congr_arg Quotient.mk'' hy)⟩
@[to_additive]
theorem index_comap (f : G' →* G) :
(H.comap f).index = H.relindex f.range :=
Eq.trans (congr_arg index (by rfl))
((H.subgroupOf f.range).index_comap_of_surjective f.rangeRestrict_surjective)
@[to_additive]
theorem relindex_comap (f : G' →* G) (K : Subgroup G') :
relindex (comap f H) K = relindex H (map f K) := by
rw [relindex, subgroupOf, comap_comap, index_comap, ← f.map_range, K.range_subtype]
variable {H K L}
@[to_additive relindex_mul_index]
theorem relindex_mul_index (h : H ≤ K) : H.relindex K * K.index = H.index :=
((mul_comm _ _).trans (Cardinal.toNat_mul _ _).symm).trans
(congr_arg Cardinal.toNat (Equiv.cardinal_eq (quotientEquivProdOfLE h))).symm
@[to_additive]
theorem index_dvd_of_le (h : H ≤ K) : K.index ∣ H.index :=
dvd_of_mul_left_eq (H.relindex K) (relindex_mul_index h)
@[to_additive]
theorem relindex_dvd_index_of_le (h : H ≤ K) : H.relindex K ∣ H.index :=
dvd_of_mul_right_eq K.index (relindex_mul_index h)
@[to_additive]
theorem relindex_subgroupOf (hKL : K ≤ L) :
(H.subgroupOf L).relindex (K.subgroupOf L) = H.relindex K :=
((index_comap (H.subgroupOf L) (inclusion hKL)).trans (congr_arg _ (inclusion_range hKL))).symm
variable (H K L)
@[to_additive relindex_mul_relindex]
theorem relindex_mul_relindex (hHK : H ≤ K) (hKL : K ≤ L) :
H.relindex K * K.relindex L = H.relindex L := by
rw [← relindex_subgroupOf hKL]
exact relindex_mul_index fun x hx => hHK hx
@[to_additive]
theorem inf_relindex_right : (H ⊓ K).relindex K = H.relindex K := by
rw [relindex, relindex, inf_subgroupOf_right]
@[to_additive]
theorem inf_relindex_left : (H ⊓ K).relindex H = K.relindex H := by
rw [inf_comm, inf_relindex_right]
@[to_additive relindex_inf_mul_relindex]
| Mathlib/GroupTheory/Index.lean | 126 | 129 | theorem relindex_inf_mul_relindex : H.relindex (K ⊓ L) * K.relindex L = (H ⊓ K).relindex L := by | rw [← inf_relindex_right H (K ⊓ L), ← inf_relindex_right K L, ← inf_relindex_right (H ⊓ K) L,
inf_assoc, relindex_mul_relindex (H ⊓ (K ⊓ L)) (K ⊓ L) L inf_le_right inf_le_right] |
/-
Copyright (c) 2021 Devon Tuma. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Devon Tuma
-/
import Mathlib.Algebra.Polynomial.Eval.Defs
import Mathlib.Analysis.Asymptotics.Lemmas
/-!
# Super-Polynomial Function Decay
This file defines a predicate `Asymptotics.SuperpolynomialDecay f` for a function satisfying
one of following equivalent definitions (The definition is in terms of the first condition):
* `x ^ n * f` tends to `𝓝 0` for all (or sufficiently large) naturals `n`
* `|x ^ n * f|` tends to `𝓝 0` for all naturals `n` (`superpolynomialDecay_iff_abs_tendsto_zero`)
* `|x ^ n * f|` is bounded for all naturals `n` (`superpolynomialDecay_iff_abs_isBoundedUnder`)
* `f` is `o(x ^ c)` for all integers `c` (`superpolynomialDecay_iff_isLittleO`)
* `f` is `O(x ^ c)` for all integers `c` (`superpolynomialDecay_iff_isBigO`)
These conditions are all equivalent to conditions in terms of polynomials, replacing `x ^ c` with
`p(x)` or `p(x)⁻¹` as appropriate, since asymptotically `p(x)` behaves like `X ^ p.natDegree`.
These further equivalences are not proven in mathlib but would be good future projects.
The definition of superpolynomial decay for `f : α → β` is relative to a parameter `k : α → β`.
Super-polynomial decay then means `f x` decays faster than `(k x) ^ c` for all integers `c`.
Equivalently `f x` decays faster than `p.eval (k x)` for all polynomials `p : β[X]`.
The definition is also relative to a filter `l : Filter α` where the decay rate is compared.
When the map `k` is given by `n ↦ ↑n : ℕ → ℝ` this defines negligible functions:
https://en.wikipedia.org/wiki/Negligible_function
When the map `k` is given by `(r₁,...,rₙ) ↦ r₁*...*rₙ : ℝⁿ → ℝ` this is equivalent
to the definition of rapidly decreasing functions given here:
https://ncatlab.org/nlab/show/rapidly+decreasing+function
# Main Theorems
* `SuperpolynomialDecay.polynomial_mul` says that if `f(x)` is negligible,
then so is `p(x) * f(x)` for any polynomial `p`.
* `superpolynomialDecay_iff_zpow_tendsto_zero` gives an equivalence between definitions in terms
of decaying faster than `k(x) ^ n` for all naturals `n` or `k(x) ^ c` for all integer `c`.
-/
namespace Asymptotics
open Topology Polynomial
open Filter
/-- `f` has superpolynomial decay in parameter `k` along filter `l` if
`k ^ n * f` tends to zero at `l` for all naturals `n` -/
def SuperpolynomialDecay {α β : Type*} [TopologicalSpace β] [CommSemiring β] (l : Filter α)
(k : α → β) (f : α → β) :=
∀ n : ℕ, Tendsto (fun a : α => k a ^ n * f a) l (𝓝 0)
variable {α β : Type*} {l : Filter α} {k : α → β} {f g g' : α → β}
section CommSemiring
variable [TopologicalSpace β] [CommSemiring β]
theorem SuperpolynomialDecay.congr' (hf : SuperpolynomialDecay l k f) (hfg : f =ᶠ[l] g) :
SuperpolynomialDecay l k g := fun z =>
(hf z).congr' (EventuallyEq.mul (EventuallyEq.refl l _) hfg)
theorem SuperpolynomialDecay.congr (hf : SuperpolynomialDecay l k f) (hfg : ∀ x, f x = g x) :
SuperpolynomialDecay l k g := fun z =>
(hf z).congr fun x => (congr_arg fun a => k x ^ z * a) <| hfg x
@[simp]
theorem superpolynomialDecay_zero (l : Filter α) (k : α → β) : SuperpolynomialDecay l k 0 :=
fun z => by simpa only [Pi.zero_apply, mul_zero] using tendsto_const_nhds
theorem SuperpolynomialDecay.add [ContinuousAdd β] (hf : SuperpolynomialDecay l k f)
(hg : SuperpolynomialDecay l k g) : SuperpolynomialDecay l k (f + g) := fun z => by
simpa only [mul_add, add_zero, Pi.add_apply] using (hf z).add (hg z)
theorem SuperpolynomialDecay.mul [ContinuousMul β] (hf : SuperpolynomialDecay l k f)
(hg : SuperpolynomialDecay l k g) : SuperpolynomialDecay l k (f * g) := fun z => by
simpa only [mul_assoc, one_mul, mul_zero, pow_zero] using (hf z).mul (hg 0)
theorem SuperpolynomialDecay.mul_const [ContinuousMul β] (hf : SuperpolynomialDecay l k f) (c : β) :
SuperpolynomialDecay l k fun n => f n * c := fun z => by
simpa only [← mul_assoc, zero_mul] using Tendsto.mul_const c (hf z)
theorem SuperpolynomialDecay.const_mul [ContinuousMul β] (hf : SuperpolynomialDecay l k f) (c : β) :
SuperpolynomialDecay l k fun n => c * f n :=
(hf.mul_const c).congr fun _ => mul_comm _ _
theorem SuperpolynomialDecay.param_mul (hf : SuperpolynomialDecay l k f) :
SuperpolynomialDecay l k (k * f) := fun z =>
tendsto_nhds.2 fun s hs hs0 =>
l.sets_of_superset ((tendsto_nhds.1 (hf <| z + 1)) s hs hs0) fun x hx => by
simpa only [Set.mem_preimage, Pi.mul_apply, ← mul_assoc, ← pow_succ] using hx
theorem SuperpolynomialDecay.mul_param (hf : SuperpolynomialDecay l k f) :
SuperpolynomialDecay l k (f * k) :=
hf.param_mul.congr fun _ => mul_comm _ _
theorem SuperpolynomialDecay.param_pow_mul (hf : SuperpolynomialDecay l k f) (n : ℕ) :
SuperpolynomialDecay l k (k ^ n * f) := by
induction n with
| zero => simpa only [one_mul, pow_zero] using hf
| succ n hn => simpa only [pow_succ', mul_assoc] using hn.param_mul
theorem SuperpolynomialDecay.mul_param_pow (hf : SuperpolynomialDecay l k f) (n : ℕ) :
SuperpolynomialDecay l k (f * k ^ n) :=
(hf.param_pow_mul n).congr fun _ => mul_comm _ _
theorem SuperpolynomialDecay.polynomial_mul [ContinuousAdd β] [ContinuousMul β]
(hf : SuperpolynomialDecay l k f) (p : β[X]) :
SuperpolynomialDecay l k fun x => (p.eval <| k x) * f x :=
Polynomial.induction_on' p (fun p q hp hq => by simpa [add_mul] using hp.add hq) fun n c => by
simpa [mul_assoc] using (hf.param_pow_mul n).const_mul c
theorem SuperpolynomialDecay.mul_polynomial [ContinuousAdd β] [ContinuousMul β]
(hf : SuperpolynomialDecay l k f) (p : β[X]) :
SuperpolynomialDecay l k fun x => f x * (p.eval <| k x) :=
(hf.polynomial_mul p).congr fun _ => mul_comm _ _
end CommSemiring
section OrderedCommSemiring
variable [TopologicalSpace β] [CommSemiring β] [PartialOrder β] [IsOrderedRing β] [OrderTopology β]
theorem SuperpolynomialDecay.trans_eventuallyLE (hk : 0 ≤ᶠ[l] k) (hg : SuperpolynomialDecay l k g)
(hg' : SuperpolynomialDecay l k g') (hfg : g ≤ᶠ[l] f) (hfg' : f ≤ᶠ[l] g') :
SuperpolynomialDecay l k f := fun z =>
tendsto_of_tendsto_of_tendsto_of_le_of_le' (hg z) (hg' z)
(hfg.mp (hk.mono fun _ hx hx' => mul_le_mul_of_nonneg_left hx' (pow_nonneg hx z)))
(hfg'.mp (hk.mono fun _ hx hx' => mul_le_mul_of_nonneg_left hx' (pow_nonneg hx z)))
end OrderedCommSemiring
section LinearOrderedCommRing
variable [TopologicalSpace β] [CommRing β] [LinearOrder β] [IsStrictOrderedRing β] [OrderTopology β]
variable (l k f)
theorem superpolynomialDecay_iff_abs_tendsto_zero :
SuperpolynomialDecay l k f ↔ ∀ n : ℕ, Tendsto (fun a : α => |k a ^ n * f a|) l (𝓝 0) :=
⟨fun h z => (tendsto_zero_iff_abs_tendsto_zero _).1 (h z), fun h z =>
(tendsto_zero_iff_abs_tendsto_zero _).2 (h z)⟩
theorem superpolynomialDecay_iff_superpolynomialDecay_abs :
SuperpolynomialDecay l k f ↔ SuperpolynomialDecay l (fun a => |k a|) fun a => |f a| :=
(superpolynomialDecay_iff_abs_tendsto_zero l k f).trans
(by simp_rw [SuperpolynomialDecay, abs_mul, abs_pow])
variable {l k f}
theorem SuperpolynomialDecay.trans_eventually_abs_le (hf : SuperpolynomialDecay l k f)
(hfg : abs ∘ g ≤ᶠ[l] abs ∘ f) : SuperpolynomialDecay l k g := by
rw [superpolynomialDecay_iff_abs_tendsto_zero] at hf ⊢
refine fun z =>
tendsto_of_tendsto_of_tendsto_of_le_of_le' tendsto_const_nhds (hf z)
(Eventually.of_forall fun x => abs_nonneg _) (hfg.mono fun x hx => ?_)
calc
|k x ^ z * g x| = |k x ^ z| * |g x| := abs_mul (k x ^ z) (g x)
_ ≤ |k x ^ z| * |f x| := by gcongr _ * ?_; exact hx
_ = |k x ^ z * f x| := (abs_mul (k x ^ z) (f x)).symm
theorem SuperpolynomialDecay.trans_abs_le (hf : SuperpolynomialDecay l k f)
(hfg : ∀ x, |g x| ≤ |f x|) : SuperpolynomialDecay l k g :=
hf.trans_eventually_abs_le (Eventually.of_forall hfg)
end LinearOrderedCommRing
section Field
variable [TopologicalSpace β] [Field β] (l k f)
theorem superpolynomialDecay_mul_const_iff [ContinuousMul β] {c : β} (hc0 : c ≠ 0) :
(SuperpolynomialDecay l k fun n => f n * c) ↔ SuperpolynomialDecay l k f :=
⟨fun h => (h.mul_const c⁻¹).congr fun x => by simp [mul_assoc, mul_inv_cancel₀ hc0], fun h =>
h.mul_const c⟩
theorem superpolynomialDecay_const_mul_iff [ContinuousMul β] {c : β} (hc0 : c ≠ 0) :
(SuperpolynomialDecay l k fun n => c * f n) ↔ SuperpolynomialDecay l k f :=
⟨fun h => (h.const_mul c⁻¹).congr fun x => by simp [← mul_assoc, inv_mul_cancel₀ hc0], fun h =>
h.const_mul c⟩
variable {l k f}
end Field
section LinearOrderedField
variable [TopologicalSpace β] [Field β] [LinearOrder β] [IsStrictOrderedRing β] [OrderTopology β]
variable (f)
theorem superpolynomialDecay_iff_abs_isBoundedUnder (hk : Tendsto k l atTop) :
SuperpolynomialDecay l k f ↔
∀ z : ℕ, IsBoundedUnder (· ≤ ·) l fun a : α => |k a ^ z * f a| := by
refine
⟨fun h z => Tendsto.isBoundedUnder_le (Tendsto.abs (h z)), fun h =>
(superpolynomialDecay_iff_abs_tendsto_zero l k f).2 fun z => ?_⟩
obtain ⟨m, hm⟩ := h (z + 1)
have h1 : Tendsto (fun _ : α => (0 : β)) l (𝓝 0) := tendsto_const_nhds
have h2 : Tendsto (fun a : α => |(k a)⁻¹| * m) l (𝓝 0) :=
zero_mul m ▸
Tendsto.mul_const m ((tendsto_zero_iff_abs_tendsto_zero _).1 hk.inv_tendsto_atTop)
refine
tendsto_of_tendsto_of_tendsto_of_le_of_le' h1 h2 (Eventually.of_forall fun x => abs_nonneg _)
((eventually_map.1 hm).mp ?_)
refine (hk.eventually_ne_atTop 0).mono fun x hk0 hx => ?_
refine Eq.trans_le ?_ (mul_le_mul_of_nonneg_left hx <| abs_nonneg (k x)⁻¹)
rw [← abs_mul, ← mul_assoc, pow_succ', ← mul_assoc, inv_mul_cancel₀ hk0, one_mul]
theorem superpolynomialDecay_iff_zpow_tendsto_zero (hk : Tendsto k l atTop) :
SuperpolynomialDecay l k f ↔ ∀ z : ℤ, Tendsto (fun a : α => k a ^ z * f a) l (𝓝 0) := by
refine ⟨fun h z => ?_, fun h n => by simpa only [zpow_natCast] using h (n : ℤ)⟩
by_cases hz : 0 ≤ z
· unfold Tendsto
lift z to ℕ using hz
simpa using h z
· have : Tendsto (fun a => k a ^ z) l (𝓝 0) :=
Tendsto.comp (tendsto_zpow_atTop_zero (not_le.1 hz)) hk
have h : Tendsto f l (𝓝 0) := by simpa using h 0
exact zero_mul (0 : β) ▸ this.mul h
variable {f}
theorem SuperpolynomialDecay.param_zpow_mul (hk : Tendsto k l atTop)
(hf : SuperpolynomialDecay l k f) (z : ℤ) :
SuperpolynomialDecay l k fun a => k a ^ z * f a := by
rw [superpolynomialDecay_iff_zpow_tendsto_zero _ hk] at hf ⊢
refine fun z' => (hf <| z' + z).congr' ((hk.eventually_ne_atTop 0).mono fun x hx => ?_)
simp [zpow_add₀ hx, mul_assoc, Pi.mul_apply]
theorem SuperpolynomialDecay.mul_param_zpow (hk : Tendsto k l atTop)
(hf : SuperpolynomialDecay l k f) (z : ℤ) : SuperpolynomialDecay l k fun a => f a * k a ^ z :=
(hf.param_zpow_mul hk z).congr fun _ => mul_comm _ _
theorem SuperpolynomialDecay.inv_param_mul (hk : Tendsto k l atTop)
(hf : SuperpolynomialDecay l k f) : SuperpolynomialDecay l k (k⁻¹ * f) := by
simpa using hf.param_zpow_mul hk (-1)
theorem SuperpolynomialDecay.param_inv_mul (hk : Tendsto k l atTop)
(hf : SuperpolynomialDecay l k f) : SuperpolynomialDecay l k (f * k⁻¹) :=
(hf.inv_param_mul hk).congr fun _ => mul_comm _ _
variable (f)
theorem superpolynomialDecay_param_mul_iff (hk : Tendsto k l atTop) :
SuperpolynomialDecay l k (k * f) ↔ SuperpolynomialDecay l k f :=
⟨fun h =>
(h.inv_param_mul hk).congr'
((hk.eventually_ne_atTop 0).mono fun x hx => by simp [← mul_assoc, inv_mul_cancel₀ hx]),
fun h => h.param_mul⟩
theorem superpolynomialDecay_mul_param_iff (hk : Tendsto k l atTop) :
SuperpolynomialDecay l k (f * k) ↔ SuperpolynomialDecay l k f := by
simpa [mul_comm k] using superpolynomialDecay_param_mul_iff f hk
theorem superpolynomialDecay_param_pow_mul_iff (hk : Tendsto k l atTop) (n : ℕ) :
SuperpolynomialDecay l k (k ^ n * f) ↔ SuperpolynomialDecay l k f := by
induction n with
| zero => simp
| succ n hn =>
simpa [pow_succ, ← mul_comm k, mul_assoc,
superpolynomialDecay_param_mul_iff (k ^ n * f) hk] using hn
theorem superpolynomialDecay_mul_param_pow_iff (hk : Tendsto k l atTop) (n : ℕ) :
SuperpolynomialDecay l k (f * k ^ n) ↔ SuperpolynomialDecay l k f := by
simpa [mul_comm f] using superpolynomialDecay_param_pow_mul_iff f hk n
variable {f}
end LinearOrderedField
section NormedLinearOrderedField
variable [NormedField β]
variable (l k f)
theorem superpolynomialDecay_iff_norm_tendsto_zero :
SuperpolynomialDecay l k f ↔ ∀ n : ℕ, Tendsto (fun a : α => ‖k a ^ n * f a‖) l (𝓝 0) :=
⟨fun h z => tendsto_zero_iff_norm_tendsto_zero.1 (h z), fun h z =>
tendsto_zero_iff_norm_tendsto_zero.2 (h z)⟩
theorem superpolynomialDecay_iff_superpolynomialDecay_norm :
SuperpolynomialDecay l k f ↔ SuperpolynomialDecay l (fun a => ‖k a‖) fun a => ‖f a‖ :=
(superpolynomialDecay_iff_norm_tendsto_zero l k f).trans (by simp [SuperpolynomialDecay])
variable {l k}
variable [LinearOrder β] [IsStrictOrderedRing β] [OrderTopology β]
| Mathlib/Analysis/Asymptotics/SuperpolynomialDecay.lean | 292 | 297 | theorem superpolynomialDecay_iff_isBigO (hk : Tendsto k l atTop) :
SuperpolynomialDecay l k f ↔ ∀ z : ℤ, f =O[l] fun a : α => k a ^ z := by | refine (superpolynomialDecay_iff_zpow_tendsto_zero f hk).trans ?_
have hk0 : ∀ᶠ x in l, k x ≠ 0 := hk.eventually_ne_atTop 0
refine ⟨fun h z => ?_, fun h z => ?_⟩
· refine isBigO_of_div_tendsto_nhds (hk0.mono fun x hx hxz ↦ absurd hxz (zpow_ne_zero _ hx)) 0 ?_ |
/-
Copyright (c) 2019 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, Yury Kudryashov, Yaël Dillies
-/
import Mathlib.Algebra.Order.BigOperators.Ring.Finset
import Mathlib.Algebra.Order.Module.OrderedSMul
import Mathlib.Algebra.Order.Module.Synonym
import Mathlib.Algebra.Ring.Action.Pointwise.Set
import Mathlib.Analysis.Convex.Star
import Mathlib.Tactic.FieldSimp
import Mathlib.Tactic.NoncommRing
import Mathlib.LinearAlgebra.AffineSpace.AffineSubspace.Defs
/-!
# Convex sets and functions in vector spaces
In a 𝕜-vector space, we define the following objects and properties.
* `Convex 𝕜 s`: A set `s` is convex if for any two points `x y ∈ s` it includes `segment 𝕜 x y`.
* `stdSimplex 𝕜 ι`: The standard simplex in `ι → 𝕜` (currently requires `Fintype ι`). It is the
intersection of the positive quadrant with the hyperplane `s.sum = 1`.
We also provide various equivalent versions of the definitions above, prove that some specific sets
are convex.
## TODO
Generalize all this file to affine spaces.
-/
variable {𝕜 E F β : Type*}
open LinearMap Set
open scoped Convex Pointwise
/-! ### Convexity of sets -/
section OrderedSemiring
variable [Semiring 𝕜] [PartialOrder 𝕜]
section AddCommMonoid
variable [AddCommMonoid E] [AddCommMonoid F]
section SMul
variable (𝕜) [SMul 𝕜 E] [SMul 𝕜 F] (s : Set E) {x : E}
/-- Convexity of sets. -/
def Convex : Prop :=
∀ ⦃x : E⦄, x ∈ s → StarConvex 𝕜 x s
variable {𝕜 s}
theorem Convex.starConvex (hs : Convex 𝕜 s) (hx : x ∈ s) : StarConvex 𝕜 x s :=
hs hx
theorem convex_iff_segment_subset : Convex 𝕜 s ↔ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → [x -[𝕜] y] ⊆ s :=
forall₂_congr fun _ _ => starConvex_iff_segment_subset
theorem Convex.segment_subset (h : Convex 𝕜 s) {x y : E} (hx : x ∈ s) (hy : y ∈ s) :
[x -[𝕜] y] ⊆ s :=
convex_iff_segment_subset.1 h hx hy
theorem Convex.openSegment_subset (h : Convex 𝕜 s) {x y : E} (hx : x ∈ s) (hy : y ∈ s) :
openSegment 𝕜 x y ⊆ s :=
(openSegment_subset_segment 𝕜 x y).trans (h.segment_subset hx hy)
/-- Alternative definition of set convexity, in terms of pointwise set operations. -/
theorem convex_iff_pointwise_add_subset :
Convex 𝕜 s ↔ ∀ ⦃a b : 𝕜⦄, 0 ≤ a → 0 ≤ b → a + b = 1 → a • s + b • s ⊆ s :=
Iff.intro
(by
rintro hA a b ha hb hab w ⟨au, ⟨u, hu, rfl⟩, bv, ⟨v, hv, rfl⟩, rfl⟩
exact hA hu hv ha hb hab)
fun h _ hx _ hy _ _ ha hb hab => (h ha hb hab) (Set.add_mem_add ⟨_, hx, rfl⟩ ⟨_, hy, rfl⟩)
alias ⟨Convex.set_combo_subset, _⟩ := convex_iff_pointwise_add_subset
theorem convex_empty : Convex 𝕜 (∅ : Set E) := fun _ => False.elim
theorem convex_univ : Convex 𝕜 (Set.univ : Set E) := fun _ _ => starConvex_univ _
theorem Convex.inter {t : Set E} (hs : Convex 𝕜 s) (ht : Convex 𝕜 t) : Convex 𝕜 (s ∩ t) :=
fun _ hx => (hs hx.1).inter (ht hx.2)
theorem convex_sInter {S : Set (Set E)} (h : ∀ s ∈ S, Convex 𝕜 s) : Convex 𝕜 (⋂₀ S) := fun _ hx =>
starConvex_sInter fun _ hs => h _ hs <| hx _ hs
theorem convex_iInter {ι : Sort*} {s : ι → Set E} (h : ∀ i, Convex 𝕜 (s i)) :
Convex 𝕜 (⋂ i, s i) :=
sInter_range s ▸ convex_sInter <| forall_mem_range.2 h
theorem convex_iInter₂ {ι : Sort*} {κ : ι → Sort*} {s : (i : ι) → κ i → Set E}
(h : ∀ i j, Convex 𝕜 (s i j)) : Convex 𝕜 (⋂ (i) (j), s i j) :=
convex_iInter fun i => convex_iInter <| h i
theorem Convex.prod {s : Set E} {t : Set F} (hs : Convex 𝕜 s) (ht : Convex 𝕜 t) :
Convex 𝕜 (s ×ˢ t) := fun _ hx => (hs hx.1).prod (ht hx.2)
theorem convex_pi {ι : Type*} {E : ι → Type*} [∀ i, AddCommMonoid (E i)] [∀ i, SMul 𝕜 (E i)]
{s : Set ι} {t : ∀ i, Set (E i)} (ht : ∀ ⦃i⦄, i ∈ s → Convex 𝕜 (t i)) : Convex 𝕜 (s.pi t) :=
fun _ hx => starConvex_pi fun _ hi => ht hi <| hx _ hi
theorem Directed.convex_iUnion {ι : Sort*} {s : ι → Set E} (hdir : Directed (· ⊆ ·) s)
(hc : ∀ ⦃i : ι⦄, Convex 𝕜 (s i)) : Convex 𝕜 (⋃ i, s i) := by
rintro x hx y hy a b ha hb hab
rw [mem_iUnion] at hx hy ⊢
obtain ⟨i, hx⟩ := hx
obtain ⟨j, hy⟩ := hy
obtain ⟨k, hik, hjk⟩ := hdir i j
exact ⟨k, hc (hik hx) (hjk hy) ha hb hab⟩
theorem DirectedOn.convex_sUnion {c : Set (Set E)} (hdir : DirectedOn (· ⊆ ·) c)
(hc : ∀ ⦃A : Set E⦄, A ∈ c → Convex 𝕜 A) : Convex 𝕜 (⋃₀ c) := by
rw [sUnion_eq_iUnion]
exact (directedOn_iff_directed.1 hdir).convex_iUnion fun A => hc A.2
end SMul
section Module
variable [Module 𝕜 E] [Module 𝕜 F] {s : Set E} {x : E}
theorem convex_iff_openSegment_subset [ZeroLEOneClass 𝕜] :
Convex 𝕜 s ↔ ∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → openSegment 𝕜 x y ⊆ s :=
forall₂_congr fun _ => starConvex_iff_openSegment_subset
theorem convex_iff_forall_pos :
Convex 𝕜 s ↔
∀ ⦃x⦄, x ∈ s → ∀ ⦃y⦄, y ∈ s → ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 → a • x + b • y ∈ s :=
forall₂_congr fun _ => starConvex_iff_forall_pos
theorem convex_iff_pairwise_pos : Convex 𝕜 s ↔
s.Pairwise fun x y => ∀ ⦃a b : 𝕜⦄, 0 < a → 0 < b → a + b = 1 → a • x + b • y ∈ s := by
refine convex_iff_forall_pos.trans ⟨fun h x hx y hy _ => h hx hy, ?_⟩
intro h x hx y hy a b ha hb hab
obtain rfl | hxy := eq_or_ne x y
· rwa [Convex.combo_self hab]
· exact h hx hy hxy ha hb hab
theorem Convex.starConvex_iff [ZeroLEOneClass 𝕜] (hs : Convex 𝕜 s) (h : s.Nonempty) :
StarConvex 𝕜 x s ↔ x ∈ s :=
⟨fun hxs => hxs.mem h, hs.starConvex⟩
protected theorem Set.Subsingleton.convex {s : Set E} (h : s.Subsingleton) : Convex 𝕜 s :=
convex_iff_pairwise_pos.mpr (h.pairwise _)
@[simp] theorem convex_singleton (c : E) : Convex 𝕜 ({c} : Set E) :=
subsingleton_singleton.convex
theorem convex_zero : Convex 𝕜 (0 : Set E) :=
convex_singleton _
theorem convex_segment [IsOrderedRing 𝕜] (x y : E) : Convex 𝕜 [x -[𝕜] y] := by
rintro p ⟨ap, bp, hap, hbp, habp, rfl⟩ q ⟨aq, bq, haq, hbq, habq, rfl⟩ a b ha hb hab
refine
⟨a * ap + b * aq, a * bp + b * bq, add_nonneg (mul_nonneg ha hap) (mul_nonneg hb haq),
add_nonneg (mul_nonneg ha hbp) (mul_nonneg hb hbq), ?_, ?_⟩
· rw [add_add_add_comm, ← mul_add, ← mul_add, habp, habq, mul_one, mul_one, hab]
· match_scalars <;> noncomm_ring
theorem Convex.linear_image (hs : Convex 𝕜 s) (f : E →ₗ[𝕜] F) : Convex 𝕜 (f '' s) := by
rintro _ ⟨x, hx, rfl⟩ _ ⟨y, hy, rfl⟩ a b ha hb hab
exact ⟨a • x + b • y, hs hx hy ha hb hab, by rw [f.map_add, f.map_smul, f.map_smul]⟩
theorem Convex.is_linear_image (hs : Convex 𝕜 s) {f : E → F} (hf : IsLinearMap 𝕜 f) :
Convex 𝕜 (f '' s) :=
hs.linear_image <| hf.mk' f
theorem Convex.linear_preimage {𝕜₁ : Type*} [Semiring 𝕜₁] [Module 𝕜₁ E] [Module 𝕜₁ F] {s : Set F}
[SMul 𝕜 𝕜₁] [IsScalarTower 𝕜 𝕜₁ E] [IsScalarTower 𝕜 𝕜₁ F] (hs : Convex 𝕜 s) (f : E →ₗ[𝕜₁] F) :
Convex 𝕜 (f ⁻¹' s) := fun x hx y hy a b ha hb hab => by
rw [mem_preimage, f.map_add, LinearMap.map_smul_of_tower, LinearMap.map_smul_of_tower]
exact hs hx hy ha hb hab
theorem Convex.is_linear_preimage {𝕜₁ : Type*} [Semiring 𝕜₁] [Module 𝕜₁ E] [Module 𝕜₁ F] {s : Set F}
[SMul 𝕜 𝕜₁] [IsScalarTower 𝕜 𝕜₁ E] [IsScalarTower 𝕜 𝕜₁ F] (hs : Convex 𝕜 s) {f : E → F}
(hf : IsLinearMap 𝕜₁ f) :
Convex 𝕜 (f ⁻¹' s) :=
hs.linear_preimage <| hf.mk' f
theorem Convex.add {t : Set E} (hs : Convex 𝕜 s) (ht : Convex 𝕜 t) : Convex 𝕜 (s + t) := by
rw [← add_image_prod]
exact (hs.prod ht).is_linear_image IsLinearMap.isLinearMap_add
variable (𝕜 E)
/-- The convex sets form an additive submonoid under pointwise addition. -/
def convexAddSubmonoid : AddSubmonoid (Set E) where
carrier := {s : Set E | Convex 𝕜 s}
zero_mem' := convex_zero
add_mem' := Convex.add
@[simp, norm_cast]
theorem coe_convexAddSubmonoid : ↑(convexAddSubmonoid 𝕜 E) = {s : Set E | Convex 𝕜 s} :=
rfl
variable {𝕜 E}
@[simp]
theorem mem_convexAddSubmonoid {s : Set E} : s ∈ convexAddSubmonoid 𝕜 E ↔ Convex 𝕜 s :=
Iff.rfl
theorem convex_list_sum {l : List (Set E)} (h : ∀ i ∈ l, Convex 𝕜 i) : Convex 𝕜 l.sum :=
(convexAddSubmonoid 𝕜 E).list_sum_mem h
theorem convex_multiset_sum {s : Multiset (Set E)} (h : ∀ i ∈ s, Convex 𝕜 i) : Convex 𝕜 s.sum :=
(convexAddSubmonoid 𝕜 E).multiset_sum_mem _ h
theorem convex_sum {ι} {s : Finset ι} (t : ι → Set E) (h : ∀ i ∈ s, Convex 𝕜 (t i)) :
Convex 𝕜 (∑ i ∈ s, t i) :=
(convexAddSubmonoid 𝕜 E).sum_mem h
theorem Convex.vadd (hs : Convex 𝕜 s) (z : E) : Convex 𝕜 (z +ᵥ s) := by
simp_rw [← image_vadd, vadd_eq_add, ← singleton_add]
exact (convex_singleton _).add hs
theorem Convex.translate (hs : Convex 𝕜 s) (z : E) : Convex 𝕜 ((fun x => z + x) '' s) :=
hs.vadd _
/-- The translation of a convex set is also convex. -/
theorem Convex.translate_preimage_right (hs : Convex 𝕜 s) (z : E) :
Convex 𝕜 ((fun x => z + x) ⁻¹' s) := by
intro x hx y hy a b ha hb hab
have h := hs hx hy ha hb hab
rwa [smul_add, smul_add, add_add_add_comm, ← add_smul, hab, one_smul] at h
/-- The translation of a convex set is also convex. -/
theorem Convex.translate_preimage_left (hs : Convex 𝕜 s) (z : E) :
Convex 𝕜 ((fun x => x + z) ⁻¹' s) := by
simpa only [add_comm] using hs.translate_preimage_right z
section OrderedAddCommMonoid
variable [AddCommMonoid β] [PartialOrder β] [IsOrderedAddMonoid β] [Module 𝕜 β] [OrderedSMul 𝕜 β]
theorem convex_Iic (r : β) : Convex 𝕜 (Iic r) := fun x hx y hy a b ha hb hab =>
calc
a • x + b • y ≤ a • r + b • r :=
add_le_add (smul_le_smul_of_nonneg_left hx ha) (smul_le_smul_of_nonneg_left hy hb)
_ = r := Convex.combo_self hab _
theorem convex_Ici (r : β) : Convex 𝕜 (Ici r) :=
convex_Iic (β := βᵒᵈ) r
theorem convex_Icc (r s : β) : Convex 𝕜 (Icc r s) :=
Ici_inter_Iic.subst ((convex_Ici r).inter <| convex_Iic s)
theorem convex_halfSpace_le {f : E → β} (h : IsLinearMap 𝕜 f) (r : β) : Convex 𝕜 { w | f w ≤ r } :=
(convex_Iic r).is_linear_preimage h
@[deprecated (since := "2024-11-12")] alias convex_halfspace_le := convex_halfSpace_le
theorem convex_halfSpace_ge {f : E → β} (h : IsLinearMap 𝕜 f) (r : β) : Convex 𝕜 { w | r ≤ f w } :=
(convex_Ici r).is_linear_preimage h
@[deprecated (since := "2024-11-12")] alias convex_halfspace_ge := convex_halfSpace_ge
theorem convex_hyperplane {f : E → β} (h : IsLinearMap 𝕜 f) (r : β) : Convex 𝕜 { w | f w = r } := by
simp_rw [le_antisymm_iff]
exact (convex_halfSpace_le h r).inter (convex_halfSpace_ge h r)
end OrderedAddCommMonoid
section OrderedCancelAddCommMonoid
variable [AddCommMonoid β] [PartialOrder β] [IsOrderedCancelAddMonoid β]
[Module 𝕜 β] [OrderedSMul 𝕜 β]
theorem convex_Iio (r : β) : Convex 𝕜 (Iio r) := by
intro x hx y hy a b ha hb hab
obtain rfl | ha' := ha.eq_or_lt
· rw [zero_add] at hab
rwa [zero_smul, zero_add, hab, one_smul]
rw [mem_Iio] at hx hy
calc
a • x + b • y < a • r + b • r := add_lt_add_of_lt_of_le
(smul_lt_smul_of_pos_left hx ha') (smul_le_smul_of_nonneg_left hy.le hb)
_ = r := Convex.combo_self hab _
theorem convex_Ioi (r : β) : Convex 𝕜 (Ioi r) :=
convex_Iio (β := βᵒᵈ) r
theorem convex_Ioo (r s : β) : Convex 𝕜 (Ioo r s) :=
Ioi_inter_Iio.subst ((convex_Ioi r).inter <| convex_Iio s)
theorem convex_Ico (r s : β) : Convex 𝕜 (Ico r s) :=
Ici_inter_Iio.subst ((convex_Ici r).inter <| convex_Iio s)
theorem convex_Ioc (r s : β) : Convex 𝕜 (Ioc r s) :=
Ioi_inter_Iic.subst ((convex_Ioi r).inter <| convex_Iic s)
theorem convex_halfSpace_lt {f : E → β} (h : IsLinearMap 𝕜 f) (r : β) : Convex 𝕜 { w | f w < r } :=
(convex_Iio r).is_linear_preimage h
@[deprecated (since := "2024-11-12")] alias convex_halfspace_lt := convex_halfSpace_lt
theorem convex_halfSpace_gt {f : E → β} (h : IsLinearMap 𝕜 f) (r : β) : Convex 𝕜 { w | r < f w } :=
(convex_Ioi r).is_linear_preimage h
@[deprecated (since := "2024-11-12")] alias convex_halfspace_gt := convex_halfSpace_gt
end OrderedCancelAddCommMonoid
section LinearOrderedAddCommMonoid
variable [AddCommMonoid β] [LinearOrder β] [IsOrderedAddMonoid β] [Module 𝕜 β] [OrderedSMul 𝕜 β]
theorem convex_uIcc (r s : β) : Convex 𝕜 (uIcc r s) :=
convex_Icc _ _
end LinearOrderedAddCommMonoid
end Module
end AddCommMonoid
section LinearOrderedAddCommMonoid
variable [AddCommMonoid E] [LinearOrder E] [IsOrderedAddMonoid E]
[PartialOrder β] [Module 𝕜 E] [OrderedSMul 𝕜 E]
{s : Set E} {f : E → β}
theorem MonotoneOn.convex_le (hf : MonotoneOn f s) (hs : Convex 𝕜 s) (r : β) :
Convex 𝕜 ({ x ∈ s | f x ≤ r }) := fun x hx y hy _ _ ha hb hab =>
⟨hs hx.1 hy.1 ha hb hab,
(hf (hs hx.1 hy.1 ha hb hab) (max_rec' s hx.1 hy.1) (Convex.combo_le_max x y ha hb hab)).trans
(max_rec' { x | f x ≤ r } hx.2 hy.2)⟩
theorem MonotoneOn.convex_lt (hf : MonotoneOn f s) (hs : Convex 𝕜 s) (r : β) :
Convex 𝕜 ({ x ∈ s | f x < r }) := fun x hx y hy _ _ ha hb hab =>
⟨hs hx.1 hy.1 ha hb hab,
(hf (hs hx.1 hy.1 ha hb hab) (max_rec' s hx.1 hy.1)
(Convex.combo_le_max x y ha hb hab)).trans_lt
(max_rec' { x | f x < r } hx.2 hy.2)⟩
theorem MonotoneOn.convex_ge (hf : MonotoneOn f s) (hs : Convex 𝕜 s) (r : β) :
Convex 𝕜 ({ x ∈ s | r ≤ f x }) :=
MonotoneOn.convex_le (E := Eᵒᵈ) (β := βᵒᵈ) hf.dual hs r
theorem MonotoneOn.convex_gt (hf : MonotoneOn f s) (hs : Convex 𝕜 s) (r : β) :
Convex 𝕜 ({ x ∈ s | r < f x }) :=
MonotoneOn.convex_lt (E := Eᵒᵈ) (β := βᵒᵈ) hf.dual hs r
theorem AntitoneOn.convex_le (hf : AntitoneOn f s) (hs : Convex 𝕜 s) (r : β) :
Convex 𝕜 ({ x ∈ s | f x ≤ r }) :=
MonotoneOn.convex_ge (β := βᵒᵈ) hf hs r
theorem AntitoneOn.convex_lt (hf : AntitoneOn f s) (hs : Convex 𝕜 s) (r : β) :
Convex 𝕜 ({ x ∈ s | f x < r }) :=
MonotoneOn.convex_gt (β := βᵒᵈ) hf hs r
theorem AntitoneOn.convex_ge (hf : AntitoneOn f s) (hs : Convex 𝕜 s) (r : β) :
Convex 𝕜 ({ x ∈ s | r ≤ f x }) :=
MonotoneOn.convex_le (β := βᵒᵈ) hf hs r
theorem AntitoneOn.convex_gt (hf : AntitoneOn f s) (hs : Convex 𝕜 s) (r : β) :
Convex 𝕜 ({ x ∈ s | r < f x }) :=
MonotoneOn.convex_lt (β := βᵒᵈ) hf hs r
theorem Monotone.convex_le (hf : Monotone f) (r : β) : Convex 𝕜 { x | f x ≤ r } :=
Set.sep_univ.subst ((hf.monotoneOn univ).convex_le convex_univ r)
theorem Monotone.convex_lt (hf : Monotone f) (r : β) : Convex 𝕜 { x | f x ≤ r } :=
Set.sep_univ.subst ((hf.monotoneOn univ).convex_le convex_univ r)
theorem Monotone.convex_ge (hf : Monotone f) (r : β) : Convex 𝕜 { x | r ≤ f x } :=
Set.sep_univ.subst ((hf.monotoneOn univ).convex_ge convex_univ r)
theorem Monotone.convex_gt (hf : Monotone f) (r : β) : Convex 𝕜 { x | f x ≤ r } :=
Set.sep_univ.subst ((hf.monotoneOn univ).convex_le convex_univ r)
theorem Antitone.convex_le (hf : Antitone f) (r : β) : Convex 𝕜 { x | f x ≤ r } :=
Set.sep_univ.subst ((hf.antitoneOn univ).convex_le convex_univ r)
theorem Antitone.convex_lt (hf : Antitone f) (r : β) : Convex 𝕜 { x | f x < r } :=
Set.sep_univ.subst ((hf.antitoneOn univ).convex_lt convex_univ r)
theorem Antitone.convex_ge (hf : Antitone f) (r : β) : Convex 𝕜 { x | r ≤ f x } :=
Set.sep_univ.subst ((hf.antitoneOn univ).convex_ge convex_univ r)
theorem Antitone.convex_gt (hf : Antitone f) (r : β) : Convex 𝕜 { x | r < f x } :=
Set.sep_univ.subst ((hf.antitoneOn univ).convex_gt convex_univ r)
end LinearOrderedAddCommMonoid
end OrderedSemiring
section OrderedCommSemiring
variable [CommSemiring 𝕜] [PartialOrder 𝕜]
section AddCommMonoid
variable [AddCommMonoid E] [AddCommMonoid F] [Module 𝕜 E] [Module 𝕜 F] {s : Set E}
theorem Convex.smul (hs : Convex 𝕜 s) (c : 𝕜) : Convex 𝕜 (c • s) :=
hs.linear_image (LinearMap.lsmul _ _ c)
theorem Convex.smul_preimage (hs : Convex 𝕜 s) (c : 𝕜) : Convex 𝕜 ((fun z => c • z) ⁻¹' s) :=
hs.linear_preimage (LinearMap.lsmul _ _ c)
theorem Convex.affinity (hs : Convex 𝕜 s) (z : E) (c : 𝕜) :
Convex 𝕜 ((fun x => z + c • x) '' s) := by
simpa only [← image_smul, ← image_vadd, image_image] using (hs.smul c).vadd z
end AddCommMonoid
end OrderedCommSemiring
section StrictOrderedCommSemiring
variable [CommSemiring 𝕜] [PartialOrder 𝕜] [IsStrictOrderedRing 𝕜] [AddCommGroup E] [Module 𝕜 E]
theorem convex_openSegment (a b : E) : Convex 𝕜 (openSegment 𝕜 a b) := by
rw [convex_iff_openSegment_subset]
rintro p ⟨ap, bp, hap, hbp, habp, rfl⟩ q ⟨aq, bq, haq, hbq, habq, rfl⟩ z ⟨a, b, ha, hb, hab, rfl⟩
refine ⟨a * ap + b * aq, a * bp + b * bq, by positivity, by positivity, ?_, ?_⟩
· linear_combination (norm := noncomm_ring) a * habp + b * habq + hab
· module
end StrictOrderedCommSemiring
section OrderedRing
variable [Ring 𝕜] [PartialOrder 𝕜]
section AddCommGroup
variable [AddCommGroup E] [AddCommGroup F] [Module 𝕜 E] [Module 𝕜 F] {s t : Set E}
@[simp]
theorem convex_vadd (a : E) : Convex 𝕜 (a +ᵥ s) ↔ Convex 𝕜 s :=
⟨fun h ↦ by simpa using h.vadd (-a), fun h ↦ h.vadd _⟩
/-- Affine subspaces are convex. -/
theorem AffineSubspace.convex (Q : AffineSubspace 𝕜 E) : Convex 𝕜 (Q : Set E) :=
fun x hx y hy a b _ _ hab ↦ by simpa [Convex.combo_eq_smul_sub_add hab] using Q.2 _ hy hx hx
/-- The preimage of a convex set under an affine map is convex. -/
theorem Convex.affine_preimage (f : E →ᵃ[𝕜] F) {s : Set F} (hs : Convex 𝕜 s) : Convex 𝕜 (f ⁻¹' s) :=
fun _ hx => (hs hx).affine_preimage _
/-- The image of a convex set under an affine map is convex. -/
theorem Convex.affine_image (f : E →ᵃ[𝕜] F) (hs : Convex 𝕜 s) : Convex 𝕜 (f '' s) := by
rintro _ ⟨x, hx, rfl⟩
exact (hs hx).affine_image _
theorem Convex.neg (hs : Convex 𝕜 s) : Convex 𝕜 (-s) :=
hs.is_linear_preimage IsLinearMap.isLinearMap_neg (𝕜₁ := 𝕜)
theorem Convex.sub (hs : Convex 𝕜 s) (ht : Convex 𝕜 t) : Convex 𝕜 (s - t) := by
rw [sub_eq_add_neg]
exact hs.add ht.neg
variable [AddRightMono 𝕜]
theorem Convex.add_smul_mem (hs : Convex 𝕜 s) {x y : E} (hx : x ∈ s) (hy : x + y ∈ s) {t : 𝕜}
(ht : t ∈ Icc (0 : 𝕜) 1) : x + t • y ∈ s := by
have h : x + t • y = (1 - t) • x + t • (x + y) := by match_scalars <;> noncomm_ring
rw [h]
exact hs hx hy (sub_nonneg_of_le ht.2) ht.1 (sub_add_cancel _ _)
| Mathlib/Analysis/Convex/Basic.lean | 465 | 467 | theorem Convex.smul_mem_of_zero_mem (hs : Convex 𝕜 s) {x : E} (zero_mem : (0 : E) ∈ s) (hx : x ∈ s)
{t : 𝕜} (ht : t ∈ Icc (0 : 𝕜) 1) : t • x ∈ s := by | simpa using hs.add_smul_mem zero_mem (by simpa using hx) ht |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jeremy Avigad, Yury Kudryashov
-/
import Mathlib.Data.Finite.Prod
import Mathlib.Data.Fintype.Pi
import Mathlib.Data.Set.Finite.Lemmas
import Mathlib.Order.ConditionallyCompleteLattice.Basic
import Mathlib.Order.Filter.CountablyGenerated
import Mathlib.Order.Filter.Ker
import Mathlib.Order.Filter.Pi
import Mathlib.Order.Filter.Prod
import Mathlib.Order.Filter.AtTopBot.Basic
/-!
# The cofinite filter
In this file we define
`Filter.cofinite`: the filter of sets with finite complement
and prove its basic properties. In particular, we prove that for `ℕ` it is equal to `Filter.atTop`.
## TODO
Define filters for other cardinalities of the complement.
-/
open Set Function
variable {ι α β : Type*} {l : Filter α}
namespace Filter
/-- The cofinite filter is the filter of subsets whose complements are finite. -/
def cofinite : Filter α :=
comk Set.Finite finite_empty (fun _t ht _s hsub ↦ ht.subset hsub) fun _ h _ ↦ h.union
@[simp]
theorem mem_cofinite {s : Set α} : s ∈ @cofinite α ↔ sᶜ.Finite :=
Iff.rfl
@[simp]
theorem eventually_cofinite {p : α → Prop} : (∀ᶠ x in cofinite, p x) ↔ { x | ¬p x }.Finite :=
Iff.rfl
theorem hasBasis_cofinite : HasBasis cofinite (fun s : Set α => s.Finite) compl :=
⟨fun s =>
⟨fun h => ⟨sᶜ, h, (compl_compl s).subset⟩, fun ⟨_t, htf, hts⟩ =>
htf.subset <| compl_subset_comm.2 hts⟩⟩
instance cofinite_neBot [Infinite α] : NeBot (@cofinite α) :=
hasBasis_cofinite.neBot_iff.2 fun hs => hs.infinite_compl.nonempty
@[simp]
| Mathlib/Order/Filter/Cofinite.lean | 57 | 58 | theorem cofinite_eq_bot_iff : @cofinite α = ⊥ ↔ Finite α := by | simp [← empty_mem_iff_bot, finite_univ_iff] |
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.AlgebraicGeometry.Morphisms.Basic
import Mathlib.RingTheory.RingHomProperties
/-!
# Constructors for properties of morphisms between schemes
This file provides some constructors to obtain morphism properties of schemes from other morphism
properties:
- `AffineTargetMorphismProperty.diagonal` : Given an affine target morphism property `P`,
`P.diagonal f` holds if `P (pullback.mapDesc f₁ f₂ f)` holds for two affine open
immersions `f₁` and `f₂`.
- `AffineTargetMorphismProperty.of`: Given a morphism property `P` of schemes,
this is the restriction of `P` to morphisms with affine target. If `P` is local at the
target, we have `(toAffineTargetMorphismProperty P).targetAffineLocally = P`
(see `MorphismProperty.targetAffineLocally_toAffineTargetMorphismProperty_eq_of_isLocalAtTarget`).
- `MorphismProperty.topologically`: Given a property `P` of maps of topological spaces,
`(topologically P) f` holds if `P` holds for the underlying continuous map of `f`.
- `MorphismProperty.stalkwise`: Given a property `P` of ring homs,
`(stalkwise P) f` holds if `P` holds for all stalk maps.
Also provides API for showing the standard locality and stability properties for these
types of properties.
-/
universe u
open TopologicalSpace CategoryTheory CategoryTheory.Limits Opposite
noncomputable section
namespace AlgebraicGeometry
section Diagonal
/-- The `AffineTargetMorphismProperty` associated to `(targetAffineLocally P).diagonal`.
See `diagonal_targetAffineLocally_eq_targetAffineLocally`.
-/
def AffineTargetMorphismProperty.diagonal (P : AffineTargetMorphismProperty) :
AffineTargetMorphismProperty :=
fun {X _} f _ =>
∀ ⦃U₁ U₂ : Scheme⦄ (f₁ : U₁ ⟶ X) (f₂ : U₂ ⟶ X) [IsAffine U₁] [IsAffine U₂] [IsOpenImmersion f₁]
[IsOpenImmersion f₂], P (pullback.mapDesc f₁ f₂ f)
instance AffineTargetMorphismProperty.diagonal_respectsIso (P : AffineTargetMorphismProperty)
[P.toProperty.RespectsIso] : P.diagonal.toProperty.RespectsIso := by
delta AffineTargetMorphismProperty.diagonal
apply AffineTargetMorphismProperty.respectsIso_mk
· introv H _ _
rw [pullback.mapDesc_comp, P.cancel_left_of_respectsIso, P.cancel_right_of_respectsIso]
apply H
· introv H _ _
rw [pullback.mapDesc_comp, P.cancel_right_of_respectsIso]
apply H
| Mathlib/AlgebraicGeometry/Morphisms/Constructors.lean | 63 | 81 | theorem HasAffineProperty.diagonal_of_openCover (P) {Q} [HasAffineProperty P Q]
{X Y : Scheme.{u}} (f : X ⟶ Y) (𝒰 : Scheme.OpenCover.{u} Y) [∀ i, IsAffine (𝒰.obj i)]
(𝒰' : ∀ i, Scheme.OpenCover.{u} (pullback f (𝒰.map i))) [∀ i j, IsAffine ((𝒰' i).obj j)]
(h𝒰' : ∀ i j k,
Q (pullback.mapDesc ((𝒰' i).map j) ((𝒰' i).map k) (𝒰.pullbackHom f i))) :
P.diagonal f := by | letI := isLocal_affineProperty P
let 𝒱 := (Scheme.Pullback.openCoverOfBase 𝒰 f f).bind fun i =>
Scheme.Pullback.openCoverOfLeftRight.{u} (𝒰' i) (𝒰' i) (pullback.snd _ _) (pullback.snd _ _)
have i1 : ∀ i, IsAffine (𝒱.obj i) := fun i => by dsimp [𝒱]; infer_instance
apply of_openCover 𝒱
rintro ⟨i, j, k⟩
dsimp [𝒱]
convert (Q.cancel_left_of_respectsIso
((pullbackDiagonalMapIso _ _ ((𝒰' i).map j) ((𝒰' i).map k)).inv ≫
pullback.map _ _ _ _ (𝟙 _) (𝟙 _) (𝟙 _) _ _) (pullback.snd _ _)).mp _ using 1
· simp
· ext1 <;> simp
· simp only [Category.assoc, limit.lift_π, PullbackCone.mk_pt, PullbackCone.mk_π_app, |
/-
Copyright (c) 2020 Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kyle Miller
-/
import Mathlib.Combinatorics.SimpleGraph.Basic
import Mathlib.Data.Fintype.Sigma
/-!
# Darts in graphs
A `Dart` or half-edge or bond in a graph is an ordered pair of adjacent vertices, regarded as an
oriented edge. This file defines darts and proves some of their basic properties.
-/
namespace SimpleGraph
variable {V : Type*} (G : SimpleGraph V)
/-- A `Dart` is an oriented edge, implemented as an ordered pair of adjacent vertices.
This terminology comes from combinatorial maps, and they are also known as "half-edges"
or "bonds." -/
structure Dart extends V × V where
adj : G.Adj fst snd
deriving DecidableEq
initialize_simps_projections Dart (+toProd, -fst, -snd)
attribute [simp] Dart.adj
variable {G}
theorem Dart.ext_iff (d₁ d₂ : G.Dart) : d₁ = d₂ ↔ d₁.toProd = d₂.toProd := by
cases d₁; cases d₂; simp
@[ext]
theorem Dart.ext (d₁ d₂ : G.Dart) (h : d₁.toProd = d₂.toProd) : d₁ = d₂ :=
(Dart.ext_iff d₁ d₂).mpr h
@[simp]
theorem Dart.fst_ne_snd (d : G.Dart) : d.fst ≠ d.snd :=
fun h ↦ G.irrefl (h ▸ d.adj)
@[simp]
theorem Dart.snd_ne_fst (d : G.Dart) : d.snd ≠ d.fst :=
fun h ↦ G.irrefl (h ▸ d.adj)
theorem Dart.toProd_injective : Function.Injective (Dart.toProd : G.Dart → V × V) :=
Dart.ext
instance Dart.fintype [Fintype V] [DecidableRel G.Adj] : Fintype G.Dart :=
Fintype.ofEquiv (Σ v, G.neighborSet v)
{ toFun := fun s => ⟨(s.fst, s.snd), s.snd.property⟩
invFun := fun d => ⟨d.fst, d.snd, d.adj⟩
left_inv := fun s => by ext <;> simp
right_inv := fun d => by ext <;> simp }
/-- The edge associated to the dart. -/
def Dart.edge (d : G.Dart) : Sym2 V :=
Sym2.mk d.toProd
@[simp]
theorem Dart.edge_mk {p : V × V} (h : G.Adj p.1 p.2) : (Dart.mk p h).edge = Sym2.mk p :=
rfl
@[simp]
theorem Dart.edge_mem (d : G.Dart) : d.edge ∈ G.edgeSet :=
d.adj
/-- The dart with reversed orientation from a given dart. -/
@[simps]
def Dart.symm (d : G.Dart) : G.Dart :=
⟨d.toProd.swap, G.symm d.adj⟩
@[simp]
theorem Dart.symm_mk {p : V × V} (h : G.Adj p.1 p.2) : (Dart.mk p h).symm = Dart.mk p.swap h.symm :=
rfl
@[simp]
theorem Dart.edge_symm (d : G.Dart) : d.symm.edge = d.edge :=
Sym2.mk_prod_swap_eq
@[simp]
theorem Dart.edge_comp_symm : Dart.edge ∘ Dart.symm = (Dart.edge : G.Dart → Sym2 V) :=
funext Dart.edge_symm
@[simp]
theorem Dart.symm_symm (d : G.Dart) : d.symm.symm = d :=
Dart.ext _ _ <| Prod.swap_swap _
@[simp]
theorem Dart.symm_involutive : Function.Involutive (Dart.symm : G.Dart → G.Dart) :=
Dart.symm_symm
theorem Dart.symm_ne (d : G.Dart) : d.symm ≠ d :=
ne_of_apply_ne (Prod.snd ∘ Dart.toProd) d.adj.ne
theorem dart_edge_eq_iff : ∀ d₁ d₂ : G.Dart, d₁.edge = d₂.edge ↔ d₁ = d₂ ∨ d₁ = d₂.symm := by
rintro ⟨p, hp⟩ ⟨q, hq⟩
simp
theorem dart_edge_eq_mk'_iff :
∀ {d : G.Dart} {p : V × V}, d.edge = Sym2.mk p ↔ d.toProd = p ∨ d.toProd = p.swap := by
rintro ⟨p, h⟩
apply Sym2.mk_eq_mk_iff
| Mathlib/Combinatorics/SimpleGraph/Dart.lean | 107 | 109 | theorem dart_edge_eq_mk'_iff' :
∀ {d : G.Dart} {u v : V},
d.edge = s(u, v) ↔ d.fst = u ∧ d.snd = v ∨ d.fst = v ∧ d.snd = u := by | |
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Filippo A. E. Nuccio
-/
import Mathlib.RingTheory.Localization.Integer
import Mathlib.RingTheory.Localization.Submodule
/-!
# Fractional ideals
This file defines fractional ideals of an integral domain and proves basic facts about them.
## Main definitions
Let `S` be a submonoid of an integral domain `R` and `P` the localization of `R` at `S`.
* `IsFractional` defines which `R`-submodules of `P` are fractional ideals
* `FractionalIdeal S P` is the type of fractional ideals in `P`
* a coercion `coeIdeal : Ideal R → FractionalIdeal S P`
* `CommSemiring (FractionalIdeal S P)` instance:
the typical ideal operations generalized to fractional ideals
* `Lattice (FractionalIdeal S P)` instance
## Main statements
* `mul_left_mono` and `mul_right_mono` state that ideal multiplication is monotone
* `mul_div_self_cancel_iff` states that `1 / I` is the inverse of `I` if one exists
## Implementation notes
Fractional ideals are considered equal when they contain the same elements,
independent of the denominator `a : R` such that `a I ⊆ R`.
Thus, we define `FractionalIdeal` to be the subtype of the predicate `IsFractional`,
instead of having `FractionalIdeal` be a structure of which `a` is a field.
Most definitions in this file specialize operations from submodules to fractional ideals,
proving that the result of this operation is fractional if the input is fractional.
Exceptions to this rule are defining `(+) := (⊔)` and `⊥ := 0`,
in order to re-use their respective proof terms.
We can still use `simp` to show `↑I + ↑J = ↑(I + J)` and `↑⊥ = ↑0`.
Many results in fact do not need that `P` is a localization, only that `P` is an
`R`-algebra. We omit the `IsLocalization` parameter whenever this is practical.
Similarly, we don't assume that the localization is a field until we need it to
define ideal quotients. When this assumption is needed, we replace `S` with `R⁰`,
making the localization a field.
## References
* https://en.wikipedia.org/wiki/Fractional_ideal
## Tags
fractional ideal, fractional ideals, invertible ideal
-/
open IsLocalization Pointwise nonZeroDivisors
section Defs
variable {R : Type*} [CommRing R] {S : Submonoid R} {P : Type*} [CommRing P]
variable [Algebra R P]
variable (S)
/-- A submodule `I` is a fractional ideal if `a I ⊆ R` for some `a ≠ 0`. -/
def IsFractional (I : Submodule R P) :=
∃ a ∈ S, ∀ b ∈ I, IsInteger R (a • b)
variable (P)
/-- The fractional ideals of a domain `R` are ideals of `R` divided by some `a ∈ R`.
More precisely, let `P` be a localization of `R` at some submonoid `S`,
then a fractional ideal `I ⊆ P` is an `R`-submodule of `P`,
such that there is a nonzero `a : R` with `a I ⊆ R`.
-/
def FractionalIdeal :=
{ I : Submodule R P // IsFractional S I }
end Defs
namespace FractionalIdeal
open Set Submodule
variable {R : Type*} [CommRing R] {S : Submonoid R} {P : Type*} [CommRing P]
variable [Algebra R P]
/-- Map a fractional ideal `I` to a submodule by forgetting that `∃ a, a I ⊆ R`.
This implements the coercion `FractionalIdeal S P → Submodule R P`.
-/
@[coe]
def coeToSubmodule (I : FractionalIdeal S P) : Submodule R P :=
I.val
/-- Map a fractional ideal `I` to a submodule by forgetting that `∃ a, a I ⊆ R`.
This coercion is typically called `coeToSubmodule` in lemma names
(or `coe` when the coercion is clear from the context),
not to be confused with `IsLocalization.coeSubmodule : Ideal R → Submodule R P`
(which we use to define `coe : Ideal R → FractionalIdeal S P`).
-/
instance : CoeOut (FractionalIdeal S P) (Submodule R P) :=
⟨coeToSubmodule⟩
protected theorem isFractional (I : FractionalIdeal S P) : IsFractional S (I : Submodule R P) :=
I.prop
/-- An element of `S` such that `I.den • I = I.num`, see `FractionalIdeal.num` and
`FractionalIdeal.den_mul_self_eq_num`. -/
noncomputable def den (I : FractionalIdeal S P) : S :=
⟨I.2.choose, I.2.choose_spec.1⟩
/-- An ideal of `R` such that `I.den • I = I.num`, see `FractionalIdeal.den` and
`FractionalIdeal.den_mul_self_eq_num`. -/
noncomputable def num (I : FractionalIdeal S P) : Ideal R :=
(I.den • (I : Submodule R P)).comap (Algebra.linearMap R P)
theorem den_mul_self_eq_num (I : FractionalIdeal S P) :
I.den • (I : Submodule R P) = Submodule.map (Algebra.linearMap R P) I.num := by
rw [den, num, Submodule.map_comap_eq]
refine (inf_of_le_right ?_).symm
rintro _ ⟨a, ha, rfl⟩
exact I.2.choose_spec.2 a ha
/-- The linear equivalence between the fractional ideal `I` and the integral ideal `I.num`
defined by mapping `x` to `den I • x`. -/
noncomputable def equivNum [Nontrivial P] [NoZeroSMulDivisors R P]
{I : FractionalIdeal S P} (h_nz : (I.den : R) ≠ 0) : I ≃ₗ[R] I.num := by
refine LinearEquiv.trans
(LinearEquiv.ofBijective ((DistribMulAction.toLinearMap R P I.den).restrict fun _ hx ↦ ?_)
⟨fun _ _ hxy ↦ ?_, fun ⟨y, hy⟩ ↦ ?_⟩)
(Submodule.equivMapOfInjective (Algebra.linearMap R P)
(FaithfulSMul.algebraMap_injective R P) (num I)).symm
· rw [← den_mul_self_eq_num]
exact Submodule.smul_mem_pointwise_smul _ _ _ hx
· simp_rw [LinearMap.restrict_apply, DistribMulAction.toLinearMap_apply, Subtype.mk.injEq] at hxy
rwa [Submonoid.smul_def, Submonoid.smul_def, smul_right_inj h_nz, SetCoe.ext_iff] at hxy
· rw [← den_mul_self_eq_num] at hy
obtain ⟨x, hx, hxy⟩ := hy
exact ⟨⟨x, hx⟩, by simp_rw [LinearMap.restrict_apply, Subtype.ext_iff, ← hxy]; rfl⟩
section SetLike
instance : SetLike (FractionalIdeal S P) P where
coe I := ↑(I : Submodule R P)
coe_injective' := SetLike.coe_injective.comp Subtype.coe_injective
@[simp]
theorem mem_coe {I : FractionalIdeal S P} {x : P} : x ∈ (I : Submodule R P) ↔ x ∈ I :=
Iff.rfl
@[ext]
theorem ext {I J : FractionalIdeal S P} : (∀ x, x ∈ I ↔ x ∈ J) → I = J :=
SetLike.ext
@[simp]
theorem equivNum_apply [Nontrivial P] [NoZeroSMulDivisors R P] {I : FractionalIdeal S P}
(h_nz : (I.den : R) ≠ 0) (x : I) :
algebraMap R P (equivNum h_nz x) = I.den • x := by
change Algebra.linearMap R P _ = _
rw [equivNum, LinearEquiv.trans_apply, LinearEquiv.ofBijective_apply, LinearMap.restrict_apply,
Submodule.map_equivMapOfInjective_symm_apply, Subtype.coe_mk,
DistribMulAction.toLinearMap_apply]
/-- Copy of a `FractionalIdeal` with a new underlying set equal to the old one.
Useful to fix definitional equalities. -/
protected def copy (p : FractionalIdeal S P) (s : Set P) (hs : s = ↑p) : FractionalIdeal S P :=
⟨Submodule.copy p s hs, by
convert p.isFractional
ext
simp only [hs]
rfl⟩
@[simp]
theorem coe_copy (p : FractionalIdeal S P) (s : Set P) (hs : s = ↑p) : ↑(p.copy s hs) = s :=
rfl
theorem coe_eq (p : FractionalIdeal S P) (s : Set P) (hs : s = ↑p) : p.copy s hs = p :=
SetLike.coe_injective hs
end SetLike
lemma zero_mem (I : FractionalIdeal S P) : 0 ∈ I := I.coeToSubmodule.zero_mem
-- Porting note: this seems to be needed a lot more than in Lean 3
@[simp]
theorem val_eq_coe (I : FractionalIdeal S P) : I.val = I :=
rfl
-- Porting note: had to rephrase this to make it clear to `simp` what was going on.
@[simp, norm_cast]
theorem coe_mk (I : Submodule R P) (hI : IsFractional S I) :
coeToSubmodule ⟨I, hI⟩ = I :=
rfl
theorem coeToSet_coeToSubmodule (I : FractionalIdeal S P) :
((I : Submodule R P) : Set P) = I :=
rfl
/-! Transfer instances from `Submodule R P` to `FractionalIdeal S P`. -/
instance (I : FractionalIdeal S P) : Module R I :=
Submodule.module (I : Submodule R P)
theorem coeToSubmodule_injective :
Function.Injective (fun (I : FractionalIdeal S P) ↦ (I : Submodule R P)) :=
Subtype.coe_injective
theorem coeToSubmodule_inj {I J : FractionalIdeal S P} : (I : Submodule R P) = J ↔ I = J :=
coeToSubmodule_injective.eq_iff
theorem isFractional_of_le_one (I : Submodule R P) (h : I ≤ 1) : IsFractional S I := by
use 1, S.one_mem
intro b hb
rw [one_smul]
obtain ⟨b', b'_mem, rfl⟩ := mem_one.mp (h hb)
exact Set.mem_range_self b'
theorem isFractional_of_le {I : Submodule R P} {J : FractionalIdeal S P} (hIJ : I ≤ J) :
IsFractional S I := by
obtain ⟨a, a_mem, ha⟩ := J.isFractional
use a, a_mem
intro b b_mem
exact ha b (hIJ b_mem)
/-- Map an ideal `I` to a fractional ideal by forgetting `I` is integral.
This is the function that implements the coercion `Ideal R → FractionalIdeal S P`. -/
@[coe]
def coeIdeal (I : Ideal R) : FractionalIdeal S P :=
⟨coeSubmodule P I,
isFractional_of_le_one _ <| by simpa using coeSubmodule_mono P (le_top : I ≤ ⊤)⟩
-- Is a `CoeTC` rather than `Coe` to speed up failing inference, see library note [use has_coe_t]
/-- Map an ideal `I` to a fractional ideal by forgetting `I` is integral.
This is a bundled version of `IsLocalization.coeSubmodule : Ideal R → Submodule R P`,
which is not to be confused with the `coe : FractionalIdeal S P → Submodule R P`,
also called `coeToSubmodule` in theorem names.
This map is available as a ring hom, called `FractionalIdeal.coeIdealHom`.
-/
instance : CoeTC (Ideal R) (FractionalIdeal S P) :=
⟨fun I => coeIdeal I⟩
@[simp, norm_cast]
theorem coe_coeIdeal (I : Ideal R) :
((I : FractionalIdeal S P) : Submodule R P) = coeSubmodule P I :=
rfl
variable (S)
@[simp]
theorem mem_coeIdeal {x : P} {I : Ideal R} :
x ∈ (I : FractionalIdeal S P) ↔ ∃ x', x' ∈ I ∧ algebraMap R P x' = x :=
mem_coeSubmodule _ _
theorem mem_coeIdeal_of_mem {x : R} {I : Ideal R} (hx : x ∈ I) :
algebraMap R P x ∈ (I : FractionalIdeal S P) :=
(mem_coeIdeal S).mpr ⟨x, hx, rfl⟩
theorem coeIdeal_le_coeIdeal' [IsLocalization S P] (h : S ≤ nonZeroDivisors R) {I J : Ideal R} :
(I : FractionalIdeal S P) ≤ J ↔ I ≤ J :=
coeSubmodule_le_coeSubmodule h
@[simp]
theorem coeIdeal_le_coeIdeal (K : Type*) [CommRing K] [Algebra R K] [IsFractionRing R K]
{I J : Ideal R} : (I : FractionalIdeal R⁰ K) ≤ J ↔ I ≤ J :=
IsFractionRing.coeSubmodule_le_coeSubmodule
instance : Zero (FractionalIdeal S P) :=
⟨(0 : Ideal R)⟩
@[simp]
theorem mem_zero_iff {x : P} : x ∈ (0 : FractionalIdeal S P) ↔ x = 0 :=
⟨fun ⟨x', x'_mem_zero, x'_eq_x⟩ => by
have x'_eq_zero : x' = 0 := x'_mem_zero
simp [x'_eq_x.symm, x'_eq_zero], fun hx => ⟨0, rfl, by simp [hx]⟩⟩
variable {S}
@[simp, norm_cast]
theorem coe_zero : ↑(0 : FractionalIdeal S P) = (⊥ : Submodule R P) :=
Submodule.ext fun _ => mem_zero_iff S
@[simp, norm_cast]
theorem coeIdeal_bot : ((⊥ : Ideal R) : FractionalIdeal S P) = 0 :=
rfl
section
variable [loc : IsLocalization S P]
variable (P) in
@[simp]
theorem exists_mem_algebraMap_eq {x : R} {I : Ideal R} (h : S ≤ nonZeroDivisors R) :
(∃ x', x' ∈ I ∧ algebraMap R P x' = algebraMap R P x) ↔ x ∈ I :=
⟨fun ⟨_, hx', Eq⟩ => IsLocalization.injective _ h Eq ▸ hx', fun h => ⟨x, h, rfl⟩⟩
theorem coeIdeal_injective' (h : S ≤ nonZeroDivisors R) :
Function.Injective (fun (I : Ideal R) ↦ (I : FractionalIdeal S P)) := fun _ _ h' =>
((coeIdeal_le_coeIdeal' S h).mp h'.le).antisymm ((coeIdeal_le_coeIdeal' S h).mp
h'.ge)
theorem coeIdeal_inj' (h : S ≤ nonZeroDivisors R) {I J : Ideal R} :
(I : FractionalIdeal S P) = J ↔ I = J :=
(coeIdeal_injective' h).eq_iff
-- Porting note: doesn't need to be @[simp] because it can be proved by coeIdeal_eq_zero
theorem coeIdeal_eq_zero' {I : Ideal R} (h : S ≤ nonZeroDivisors R) :
(I : FractionalIdeal S P) = 0 ↔ I = (⊥ : Ideal R) :=
coeIdeal_inj' h
theorem coeIdeal_ne_zero' {I : Ideal R} (h : S ≤ nonZeroDivisors R) :
(I : FractionalIdeal S P) ≠ 0 ↔ I ≠ (⊥ : Ideal R) :=
not_iff_not.mpr <| coeIdeal_eq_zero' h
end
theorem coeToSubmodule_eq_bot {I : FractionalIdeal S P} : (I : Submodule R P) = ⊥ ↔ I = 0 :=
⟨fun h => coeToSubmodule_injective (by simp [h]), fun h => by simp [h]⟩
theorem coeToSubmodule_ne_bot {I : FractionalIdeal S P} : ↑I ≠ (⊥ : Submodule R P) ↔ I ≠ 0 :=
not_iff_not.mpr coeToSubmodule_eq_bot
instance : Inhabited (FractionalIdeal S P) :=
⟨0⟩
instance : One (FractionalIdeal S P) :=
⟨(⊤ : Ideal R)⟩
theorem zero_of_num_eq_bot [NoZeroSMulDivisors R P] (hS : 0 ∉ S) {I : FractionalIdeal S P}
(hI : I.num = ⊥) : I = 0 := by
rw [← coeToSubmodule_eq_bot, eq_bot_iff]
intro x hx
suffices (den I : R) • x = 0 from
(smul_eq_zero.mp this).resolve_left (ne_of_mem_of_not_mem (SetLike.coe_mem _) hS)
have h_eq : I.den • (I : Submodule R P) = ⊥ := by rw [den_mul_self_eq_num, hI, Submodule.map_bot]
exact (Submodule.eq_bot_iff _).mp h_eq (den I • x) ⟨x, hx, rfl⟩
theorem num_zero_eq (h_inj : Function.Injective (algebraMap R P)) :
num (0 : FractionalIdeal S P) = 0 := by
simpa [num, LinearMap.ker_eq_bot] using h_inj
variable (S)
@[simp, norm_cast]
theorem coeIdeal_top : ((⊤ : Ideal R) : FractionalIdeal S P) = 1 :=
rfl
theorem mem_one_iff {x : P} : x ∈ (1 : FractionalIdeal S P) ↔ ∃ x' : R, algebraMap R P x' = x :=
Iff.intro (fun ⟨x', _, h⟩ => ⟨x', h⟩) fun ⟨x', h⟩ => ⟨x', ⟨⟩, h⟩
theorem coe_mem_one (x : R) : algebraMap R P x ∈ (1 : FractionalIdeal S P) :=
(mem_one_iff S).mpr ⟨x, rfl⟩
theorem one_mem_one : (1 : P) ∈ (1 : FractionalIdeal S P) :=
(mem_one_iff S).mpr ⟨1, RingHom.map_one _⟩
variable {S}
/-- `(1 : FractionalIdeal S P)` is defined as the R-submodule `f(R) ≤ P`.
However, this is not definitionally equal to `1 : Submodule R P`,
which is proved in the actual `simp` lemma `coe_one`. -/
theorem coe_one_eq_coeSubmodule_top : ↑(1 : FractionalIdeal S P) = coeSubmodule P (⊤ : Ideal R) :=
rfl
@[simp, norm_cast]
| Mathlib/RingTheory/FractionalIdeal/Basic.lean | 371 | 373 | theorem coe_one : (↑(1 : FractionalIdeal S P) : Submodule R P) = 1 := by | rw [coe_one_eq_coeSubmodule_top, coeSubmodule_top] |
/-
Copyright (c) 2020 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta, Edward Ayers
-/
import Mathlib.CategoryTheory.Limits.Shapes.Pullback.HasPullback
import Mathlib.Data.Set.BooleanAlgebra
/-!
# Theory of sieves
- For an object `X` of a category `C`, a `Sieve X` is a set of morphisms to `X`
which is closed under left-composition.
- The complete lattice structure on sieves is given, as well as the Galois insertion
given by downward-closing.
- A `Sieve X` (functorially) induces a presheaf on `C` together with a monomorphism to
the yoneda embedding of `X`.
## Tags
sieve, pullback
-/
universe v₁ v₂ v₃ u₁ u₂ u₃
namespace CategoryTheory
open Category Limits
variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D] (F : C ⥤ D)
variable {X Y Z : C} (f : Y ⟶ X)
/-- A set of arrows all with codomain `X`. -/
def Presieve (X : C) :=
∀ ⦃Y⦄, Set (Y ⟶ X)-- deriving CompleteLattice
instance : CompleteLattice (Presieve X) := by
dsimp [Presieve]
infer_instance
namespace Presieve
noncomputable instance : Inhabited (Presieve X) :=
⟨⊤⟩
/-- The full subcategory of the over category `C/X` consisting of arrows which belong to a
presieve on `X`. -/
abbrev category {X : C} (P : Presieve X) :=
ObjectProperty.FullSubcategory fun f : Over X => P f.hom
/-- Construct an object of `P.category`. -/
abbrev categoryMk {X : C} (P : Presieve X) {Y : C} (f : Y ⟶ X) (hf : P f) : P.category :=
⟨Over.mk f, hf⟩
/-- Given a sieve `S` on `X : C`, its associated diagram `S.diagram` is defined to be
the natural functor from the full subcategory of the over category `C/X` consisting
of arrows in `S` to `C`. -/
abbrev diagram (S : Presieve X) : S.category ⥤ C :=
ObjectProperty.ι _ ⋙ Over.forget X
/-- Given a sieve `S` on `X : C`, its associated cocone `S.cocone` is defined to be
the natural cocone over the diagram defined above with cocone point `X`. -/
abbrev cocone (S : Presieve X) : Cocone S.diagram :=
(Over.forgetCocone X).whisker (ObjectProperty.ι _)
/-- Given a set of arrows `S` all with codomain `X`, and a set of arrows with codomain `Y` for each
`f : Y ⟶ X` in `S`, produce a set of arrows with codomain `X`:
`{ g ≫ f | (f : Y ⟶ X) ∈ S, (g : Z ⟶ Y) ∈ R f }`.
-/
def bind (S : Presieve X) (R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y) : Presieve X := fun Z h =>
∃ (Y : C) (g : Z ⟶ Y) (f : Y ⟶ X) (H : S f), R H g ∧ g ≫ f = h
/-- Structure which contains the data and properties for a morphism `h` satisfying
`Presieve.bind S R h`. -/
structure BindStruct (S : Presieve X) (R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y)
{Z : C} (h : Z ⟶ X) where
/-- the intermediate object -/
Y : C
/-- a morphism in the family of presieves `R` -/
g : Z ⟶ Y
/-- a morphism in the presieve `S` -/
f : Y ⟶ X
hf : S f
hg : R hf g
fac : g ≫ f = h
attribute [reassoc (attr := simp)] BindStruct.fac
/-- If a morphism `h` satisfies `Presieve.bind S R h`, this is a choice of a structure
in `BindStruct S R h`. -/
noncomputable def bind.bindStruct {S : Presieve X} {R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y}
{Z : C} {h : Z ⟶ X} (H : bind S R h) : BindStruct S R h :=
Nonempty.some (by
obtain ⟨Y, g, f, hf, hg, fac⟩ := H
exact ⟨{ hf := hf, hg := hg, fac := fac, .. }⟩)
lemma BindStruct.bind {S : Presieve X} {R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y}
{Z : C} {h : Z ⟶ X} (b : BindStruct S R h) : bind S R h :=
⟨b.Y, b.g, b.f, b.hf, b.hg, b.fac⟩
@[simp]
theorem bind_comp {S : Presieve X} {R : ∀ ⦃Y : C⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y} {g : Z ⟶ Y}
(h₁ : S f) (h₂ : R h₁ g) : bind S R (g ≫ f) :=
⟨_, _, _, h₁, h₂, rfl⟩
-- Porting note: it seems the definition of `Presieve` must be unfolded in order to define
-- this inductive type, it was thus renamed `singleton'`
-- Note we can't make this into `HasSingleton` because of the out-param.
/-- The singleton presieve. -/
inductive singleton' : ⦃Y : C⦄ → (Y ⟶ X) → Prop
| mk : singleton' f
/-- The singleton presieve. -/
def singleton : Presieve X := singleton' f
lemma singleton.mk {f : Y ⟶ X} : singleton f f := singleton'.mk
@[simp]
theorem singleton_eq_iff_domain (f g : Y ⟶ X) : singleton f g ↔ f = g := by
constructor
· rintro ⟨a, rfl⟩
rfl
· rintro rfl
apply singleton.mk
theorem singleton_self : singleton f f :=
singleton.mk
/-- Pullback a set of arrows with given codomain along a fixed map, by taking the pullback in the
category.
This is not the same as the arrow set of `Sieve.pullback`, but there is a relation between them
in `pullbackArrows_comm`.
-/
inductive pullbackArrows [HasPullbacks C] (R : Presieve X) : Presieve Y
| mk (Z : C) (h : Z ⟶ X) : R h → pullbackArrows _ (pullback.snd h f)
theorem pullback_singleton [HasPullbacks C] (g : Z ⟶ X) :
pullbackArrows f (singleton g) = singleton (pullback.snd g f) := by
funext W
ext h
constructor
· rintro ⟨W, _, _, _⟩
exact singleton.mk
· rintro ⟨_⟩
exact pullbackArrows.mk Z g singleton.mk
/-- Construct the presieve given by the family of arrows indexed by `ι`. -/
inductive ofArrows {ι : Type*} (Y : ι → C) (f : ∀ i, Y i ⟶ X) : Presieve X
| mk (i : ι) : ofArrows _ _ (f i)
theorem ofArrows_pUnit : (ofArrows _ fun _ : PUnit => f) = singleton f := by
funext Y
ext g
constructor
· rintro ⟨_⟩
apply singleton.mk
· rintro ⟨_⟩
exact ofArrows.mk PUnit.unit
theorem ofArrows_pullback [HasPullbacks C] {ι : Type*} (Z : ι → C) (g : ∀ i : ι, Z i ⟶ X) :
(ofArrows (fun i => pullback (g i) f) fun _ => pullback.snd _ _) =
pullbackArrows f (ofArrows Z g) := by
funext T
ext h
constructor
· rintro ⟨hk⟩
exact pullbackArrows.mk _ _ (ofArrows.mk hk)
· rintro ⟨W, k, ⟨_⟩⟩
apply ofArrows.mk
theorem ofArrows_bind {ι : Type*} (Z : ι → C) (g : ∀ i : ι, Z i ⟶ X)
(j : ∀ ⦃Y⦄ (f : Y ⟶ X), ofArrows Z g f → Type*) (W : ∀ ⦃Y⦄ (f : Y ⟶ X) (H), j f H → C)
(k : ∀ ⦃Y⦄ (f : Y ⟶ X) (H i), W f H i ⟶ Y) :
((ofArrows Z g).bind fun _ f H => ofArrows (W f H) (k f H)) =
ofArrows (fun i : Σi, j _ (ofArrows.mk i) => W (g i.1) _ i.2) fun ij =>
k (g ij.1) _ ij.2 ≫ g ij.1 := by
funext Y
ext f
constructor
· rintro ⟨_, _, _, ⟨i⟩, ⟨i'⟩, rfl⟩
exact ofArrows.mk (Sigma.mk _ _)
· rintro ⟨i⟩
exact bind_comp _ (ofArrows.mk _) (ofArrows.mk _)
theorem ofArrows_surj {ι : Type*} {Y : ι → C} (f : ∀ i, Y i ⟶ X) {Z : C} (g : Z ⟶ X)
(hg : ofArrows Y f g) : ∃ (i : ι) (h : Y i = Z),
g = eqToHom h.symm ≫ f i := by
obtain ⟨i⟩ := hg
exact ⟨i, rfl, by simp only [eqToHom_refl, id_comp]⟩
/-- Given a presieve on `F(X)`, we can define a presieve on `X` by taking the preimage via `F`. -/
def functorPullback (R : Presieve (F.obj X)) : Presieve X := fun _ f => R (F.map f)
@[simp]
theorem functorPullback_mem (R : Presieve (F.obj X)) {Y} (f : Y ⟶ X) :
R.functorPullback F f ↔ R (F.map f) :=
Iff.rfl
@[simp]
theorem functorPullback_id (R : Presieve X) : R.functorPullback (𝟭 _) = R :=
rfl
/-- Given a presieve `R` on `X`, the predicate `R.hasPullbacks` means that for all arrows `f` and
`g` in `R`, the pullback of `f` and `g` exists. -/
class hasPullbacks (R : Presieve X) : Prop where
/-- For all arrows `f` and `g` in `R`, the pullback of `f` and `g` exists. -/
has_pullbacks : ∀ {Y Z} {f : Y ⟶ X} (_ : R f) {g : Z ⟶ X} (_ : R g), HasPullback f g
instance (R : Presieve X) [HasPullbacks C] : R.hasPullbacks := ⟨fun _ _ ↦ inferInstance⟩
instance {α : Type v₂} {X : α → C} {B : C} (π : (a : α) → X a ⟶ B)
[(Presieve.ofArrows X π).hasPullbacks] (a b : α) : HasPullback (π a) (π b) :=
Presieve.hasPullbacks.has_pullbacks (Presieve.ofArrows.mk _) (Presieve.ofArrows.mk _)
section FunctorPushforward
variable {E : Type u₃} [Category.{v₃} E] (G : D ⥤ E)
/-- Given a presieve on `X`, we can define a presieve on `F(X)` (which is actually a sieve)
by taking the sieve generated by the image via `F`.
-/
def functorPushforward (S : Presieve X) : Presieve (F.obj X) := fun Y f =>
∃ (Z : C) (g : Z ⟶ X) (h : Y ⟶ F.obj Z), S g ∧ f = h ≫ F.map g
/-- An auxiliary definition in order to fix the choice of the preimages between various definitions.
-/
structure FunctorPushforwardStructure (S : Presieve X) {Y} (f : Y ⟶ F.obj X) where
/-- an object in the source category -/
preobj : C
/-- a map in the source category which has to be in the presieve -/
premap : preobj ⟶ X
/-- the morphism which appear in the factorisation -/
lift : Y ⟶ F.obj preobj
/-- the condition that `premap` is in the presieve -/
cover : S premap
/-- the factorisation of the morphism -/
fac : f = lift ≫ F.map premap
/-- The fixed choice of a preimage. -/
noncomputable def getFunctorPushforwardStructure {F : C ⥤ D} {S : Presieve X} {Y : D}
{f : Y ⟶ F.obj X} (h : S.functorPushforward F f) : FunctorPushforwardStructure F S f := by
choose Z f' g h₁ h using h
exact ⟨Z, f', g, h₁, h⟩
theorem functorPushforward_comp (R : Presieve X) :
R.functorPushforward (F ⋙ G) = (R.functorPushforward F).functorPushforward G := by
funext x
ext f
constructor
· rintro ⟨X, f₁, g₁, h₁, rfl⟩
exact ⟨F.obj X, F.map f₁, g₁, ⟨X, f₁, 𝟙 _, h₁, by simp⟩, rfl⟩
· rintro ⟨X, f₁, g₁, ⟨X', f₂, g₂, h₁, rfl⟩, rfl⟩
exact ⟨X', f₂, g₁ ≫ G.map g₂, h₁, by simp⟩
theorem image_mem_functorPushforward (R : Presieve X) {f : Y ⟶ X} (h : R f) :
R.functorPushforward F (F.map f) :=
⟨Y, f, 𝟙 _, h, by simp⟩
end FunctorPushforward
end Presieve
/--
For an object `X` of a category `C`, a `Sieve X` is a set of morphisms to `X` which is closed under
left-composition.
-/
structure Sieve {C : Type u₁} [Category.{v₁} C] (X : C) where
/-- the underlying presieve -/
arrows : Presieve X
/-- stability by precomposition -/
downward_closed : ∀ {Y Z f} (_ : arrows f) (g : Z ⟶ Y), arrows (g ≫ f)
namespace Sieve
instance : CoeFun (Sieve X) fun _ => Presieve X :=
⟨Sieve.arrows⟩
initialize_simps_projections Sieve (arrows → apply)
variable {S R : Sieve X}
attribute [simp] downward_closed
theorem arrows_ext : ∀ {R S : Sieve X}, R.arrows = S.arrows → R = S := by
rintro ⟨_, _⟩ ⟨_, _⟩ rfl
rfl
@[ext]
protected theorem ext {R S : Sieve X} (h : ∀ ⦃Y⦄ (f : Y ⟶ X), R f ↔ S f) : R = S :=
arrows_ext <| funext fun _ => funext fun f => propext <| h f
open Lattice
/-- The supremum of a collection of sieves: the union of them all. -/
protected def sup (𝒮 : Set (Sieve X)) : Sieve X where
arrows _ := { f | ∃ S ∈ 𝒮, Sieve.arrows S f }
downward_closed {_ _ f} hf _ := by
obtain ⟨S, hS, hf⟩ := hf
exact ⟨S, hS, S.downward_closed hf _⟩
/-- The infimum of a collection of sieves: the intersection of them all. -/
protected def inf (𝒮 : Set (Sieve X)) : Sieve X where
arrows _ := { f | ∀ S ∈ 𝒮, Sieve.arrows S f }
downward_closed {_ _ _} hf g S H := S.downward_closed (hf S H) g
/-- The union of two sieves is a sieve. -/
protected def union (S R : Sieve X) : Sieve X where
arrows _ f := S f ∨ R f
downward_closed := by rintro _ _ _ (h | h) g <;> simp [h]
/-- The intersection of two sieves is a sieve. -/
protected def inter (S R : Sieve X) : Sieve X where
arrows _ f := S f ∧ R f
downward_closed := by
rintro _ _ _ ⟨h₁, h₂⟩ g
simp [h₁, h₂]
/-- Sieves on an object `X` form a complete lattice.
We generate this directly rather than using the galois insertion for nicer definitional properties.
-/
instance : CompleteLattice (Sieve X) where
le S R := ∀ ⦃Y⦄ (f : Y ⟶ X), S f → R f
le_refl _ _ _ := id
le_trans _ _ _ S₁₂ S₂₃ _ _ h := S₂₃ _ (S₁₂ _ h)
le_antisymm _ _ p q := Sieve.ext fun _ _ => ⟨p _, q _⟩
top :=
{ arrows := fun _ => Set.univ
downward_closed := fun _ _ => ⟨⟩ }
bot :=
{ arrows := fun _ => ∅
downward_closed := False.elim }
sup := Sieve.union
inf := Sieve.inter
sSup := Sieve.sup
sInf := Sieve.inf
le_sSup _ S hS _ _ hf := ⟨S, hS, hf⟩
sSup_le := fun _ _ ha _ _ ⟨b, hb, hf⟩ => (ha b hb) _ hf
sInf_le _ _ hS _ _ h := h _ hS
le_sInf _ _ hS _ _ hf _ hR := hS _ hR _ hf
le_sup_left _ _ _ _ := Or.inl
le_sup_right _ _ _ _ := Or.inr
sup_le _ _ _ h₁ h₂ _ f := by--ℰ S hS Y f := by
rintro (hf | hf)
· exact h₁ _ hf
· exact h₂ _ hf
inf_le_left _ _ _ _ := And.left
inf_le_right _ _ _ _ := And.right
le_inf _ _ _ p q _ _ z := ⟨p _ z, q _ z⟩
le_top _ _ _ _ := trivial
bot_le _ _ _ := False.elim
/-- The maximal sieve always exists. -/
instance sieveInhabited : Inhabited (Sieve X) :=
⟨⊤⟩
@[simp]
theorem sInf_apply {Ss : Set (Sieve X)} {Y} (f : Y ⟶ X) :
sInf Ss f ↔ ∀ (S : Sieve X) (_ : S ∈ Ss), S f :=
Iff.rfl
@[simp]
theorem sSup_apply {Ss : Set (Sieve X)} {Y} (f : Y ⟶ X) :
sSup Ss f ↔ ∃ (S : Sieve X) (_ : S ∈ Ss), S f := by
simp [sSup, Sieve.sup, setOf]
@[simp]
theorem inter_apply {R S : Sieve X} {Y} (f : Y ⟶ X) : (R ⊓ S) f ↔ R f ∧ S f :=
Iff.rfl
@[simp]
theorem union_apply {R S : Sieve X} {Y} (f : Y ⟶ X) : (R ⊔ S) f ↔ R f ∨ S f :=
Iff.rfl
@[simp]
theorem top_apply (f : Y ⟶ X) : (⊤ : Sieve X) f :=
trivial
/-- Generate the smallest sieve containing the given set of arrows. -/
@[simps]
def generate (R : Presieve X) : Sieve X where
arrows Z f := ∃ (Y : _) (h : Z ⟶ Y) (g : Y ⟶ X), R g ∧ h ≫ g = f
downward_closed := by
rintro Y Z _ ⟨W, g, f, hf, rfl⟩ h
exact ⟨_, h ≫ g, _, hf, by simp⟩
/-- Given a presieve on `X`, and a sieve on each domain of an arrow in the presieve, we can bind to
produce a sieve on `X`.
-/
@[simps]
def bind (S : Presieve X) (R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Sieve Y) : Sieve X where
arrows := S.bind fun _ _ h => R h
downward_closed := by
rintro Y Z f ⟨W, f, h, hh, hf, rfl⟩ g
exact ⟨_, g ≫ f, _, hh, by simp [hf]⟩
/-- Structure which contains the data and properties for a morphism `h` satisfying
`Sieve.bind S R h`. -/
abbrev BindStruct (S : Presieve X) (R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Sieve Y)
{Z : C} (h : Z ⟶ X) :=
Presieve.BindStruct S (fun _ _ hf ↦ R hf) h
open Order Lattice
theorem generate_le_iff (R : Presieve X) (S : Sieve X) : generate R ≤ S ↔ R ≤ S :=
⟨fun H _ _ hg => H _ ⟨_, 𝟙 _, _, hg, id_comp _⟩, fun ss Y f => by
rintro ⟨Z, f, g, hg, rfl⟩
exact S.downward_closed (ss Z hg) f⟩
/-- Show that there is a galois insertion (generate, set_over). -/
def giGenerate : GaloisInsertion (generate : Presieve X → Sieve X) arrows where
gc := generate_le_iff
choice 𝒢 _ := generate 𝒢
choice_eq _ _ := rfl
le_l_u _ _ _ hf := ⟨_, 𝟙 _, _, hf, id_comp _⟩
theorem le_generate (R : Presieve X) : R ≤ generate R :=
giGenerate.gc.le_u_l R
@[simp]
theorem generate_sieve (S : Sieve X) : generate S = S :=
giGenerate.l_u_eq S
/-- If the identity arrow is in a sieve, the sieve is maximal. -/
theorem id_mem_iff_eq_top : S (𝟙 X) ↔ S = ⊤ :=
⟨fun h => top_unique fun Y f _ => by simpa using downward_closed _ h f, fun h => h.symm ▸ trivial⟩
/-- If an arrow set contains a split epi, it generates the maximal sieve. -/
theorem generate_of_contains_isSplitEpi {R : Presieve X} (f : Y ⟶ X) [IsSplitEpi f] (hf : R f) :
generate R = ⊤ := by
rw [← id_mem_iff_eq_top]
exact ⟨_, section_ f, f, hf, by simp⟩
@[simp]
theorem generate_of_singleton_isSplitEpi (f : Y ⟶ X) [IsSplitEpi f] :
generate (Presieve.singleton f) = ⊤ :=
generate_of_contains_isSplitEpi f (Presieve.singleton_self _)
@[simp]
theorem generate_top : generate (⊤ : Presieve X) = ⊤ :=
generate_of_contains_isSplitEpi (𝟙 _) ⟨⟩
@[simp]
lemma comp_mem_iff (i : X ⟶ Y) (f : Y ⟶ Z) [IsIso i] (S : Sieve Z) :
S (i ≫ f) ↔ S f := by
refine ⟨fun H ↦ ?_, fun H ↦ S.downward_closed H _⟩
convert S.downward_closed H (inv i)
simp
section
variable {I : Type*} {X : C} (Y : I → C) (f : ∀ i, Y i ⟶ X)
/-- The sieve of `X` generated by family of morphisms `Y i ⟶ X`. -/
abbrev ofArrows : Sieve X := generate (Presieve.ofArrows Y f)
lemma ofArrows_mk (i : I) : ofArrows Y f (f i) :=
⟨_, 𝟙 _, _, ⟨i⟩, by simp⟩
lemma mem_ofArrows_iff {W : C} (g : W ⟶ X) :
ofArrows Y f g ↔ ∃ (i : I) (a : W ⟶ Y i), g = a ≫ f i := by
constructor
· rintro ⟨T, a, b, ⟨i⟩, rfl⟩
exact ⟨i, a, rfl⟩
· rintro ⟨i, a, rfl⟩
apply downward_closed _ (ofArrows_mk Y f i)
variable {Y f} {W : C} {g : W ⟶ X} (hg : ofArrows Y f g)
include hg in
lemma ofArrows.exists : ∃ (i : I) (h : W ⟶ Y i), g = h ≫ f i := by
obtain ⟨_, h, _, ⟨i⟩, rfl⟩ := hg
exact ⟨i, h, rfl⟩
/-- When `hg : Sieve.ofArrows Y f g`, this is a choice of `i` such that `g`
factors through `f i`. -/
noncomputable def ofArrows.i : I := (ofArrows.exists hg).choose
/-- When `hg : Sieve.ofArrows Y f g`, this is a morphism `h : W ⟶ Y (i hg)` such
that `h ≫ f (i hg) = g`. -/
noncomputable def ofArrows.h : W ⟶ Y (i hg) := (ofArrows.exists hg).choose_spec.choose
@[reassoc (attr := simp)]
lemma ofArrows.fac : h hg ≫ f (i hg) = g :=
(ofArrows.exists hg).choose_spec.choose_spec.symm
end
/-- The sieve generated by two morphisms. -/
abbrev ofTwoArrows {U V X : C} (i : U ⟶ X) (j : V ⟶ X) : Sieve X :=
Sieve.ofArrows (Y := pairFunction U V) (fun k ↦ WalkingPair.casesOn k i j)
/-- The sieve of `X : C` that is generated by a family of objects `Y : I → C`:
it consists of morphisms to `X` which factor through at least one of the `Y i`. -/
def ofObjects {I : Type*} (Y : I → C) (X : C) : Sieve X where
arrows Z _ := ∃ (i : I), Nonempty (Z ⟶ Y i)
downward_closed := by
rintro Z₁ Z₂ p ⟨i, ⟨f⟩⟩ g
exact ⟨i, ⟨g ≫ f⟩⟩
lemma mem_ofObjects_iff {I : Type*} (Y : I → C) {Z X : C} (g : Z ⟶ X) :
ofObjects Y X g ↔ ∃ (i : I), Nonempty (Z ⟶ Y i) := by rfl
lemma ofArrows_le_ofObjects
{I : Type*} (Y : I → C) {X : C} (f : ∀ i, Y i ⟶ X) :
Sieve.ofArrows Y f ≤ Sieve.ofObjects Y X := by
intro W g hg
rw [mem_ofArrows_iff] at hg
obtain ⟨i, a, rfl⟩ := hg
exact ⟨i, ⟨a⟩⟩
lemma ofArrows_eq_ofObjects {X : C} (hX : IsTerminal X)
{I : Type*} (Y : I → C) (f : ∀ i, Y i ⟶ X) :
ofArrows Y f = ofObjects Y X := by
refine le_antisymm (ofArrows_le_ofObjects Y f) (fun W g => ?_)
rw [mem_ofArrows_iff, mem_ofObjects_iff]
rintro ⟨i, ⟨h⟩⟩
exact ⟨i, h, hX.hom_ext _ _⟩
/-- Given a morphism `h : Y ⟶ X`, send a sieve S on X to a sieve on Y
as the inverse image of S with `_ ≫ h`.
That is, `Sieve.pullback S h := (≫ h) '⁻¹ S`. -/
@[simps]
def pullback (h : Y ⟶ X) (S : Sieve X) : Sieve Y where
arrows _ sl := S (sl ≫ h)
downward_closed g := by simp [g]
@[simp]
theorem pullback_id : S.pullback (𝟙 _) = S := by simp [Sieve.ext_iff]
@[simp]
theorem pullback_top {f : Y ⟶ X} : (⊤ : Sieve X).pullback f = ⊤ :=
top_unique fun _ _ => id
| Mathlib/CategoryTheory/Sites/Sieves.lean | 535 | 536 | theorem pullback_comp {f : Y ⟶ X} {g : Z ⟶ Y} (S : Sieve X) :
S.pullback (g ≫ f) = (S.pullback f).pullback g := by | simp [Sieve.ext_iff] |
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Chris Hughes, Anne Baanen
-/
import Mathlib.Data.Matrix.Basic
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.Data.Matrix.RowCol
import Mathlib.GroupTheory.GroupAction.Ring
import Mathlib.GroupTheory.Perm.Fin
import Mathlib.LinearAlgebra.Alternating.Basic
import Mathlib.LinearAlgebra.Matrix.SemiringInverse
/-!
# Determinant of a matrix
This file defines the determinant of a matrix, `Matrix.det`, and its essential properties.
## Main definitions
- `Matrix.det`: the determinant of a square matrix, as a sum over permutations
- `Matrix.detRowAlternating`: the determinant, as an `AlternatingMap` in the rows of the matrix
## Main results
- `det_mul`: the determinant of `A * B` is the product of determinants
- `det_zero_of_row_eq`: the determinant is zero if there is a repeated row
- `det_block_diagonal`: the determinant of a block diagonal matrix is a product
of the blocks' determinants
## Implementation notes
It is possible to configure `simp` to compute determinants. See the file
`MathlibTest/matrix.lean` for some examples.
-/
universe u v w z
open Equiv Equiv.Perm Finset Function
namespace Matrix
variable {m n : Type*} [DecidableEq n] [Fintype n] [DecidableEq m] [Fintype m]
variable {R : Type v} [CommRing R]
local notation "ε " σ:arg => ((sign σ : ℤ) : R)
/-- `det` is an `AlternatingMap` in the rows of the matrix. -/
def detRowAlternating : (n → R) [⋀^n]→ₗ[R] R :=
MultilinearMap.alternatization ((MultilinearMap.mkPiAlgebra R n R).compLinearMap LinearMap.proj)
/-- The determinant of a matrix given by the Leibniz formula. -/
abbrev det (M : Matrix n n R) : R :=
detRowAlternating M
theorem det_apply (M : Matrix n n R) : M.det = ∑ σ : Perm n, Equiv.Perm.sign σ • ∏ i, M (σ i) i :=
MultilinearMap.alternatization_apply _ M
-- This is what the old definition was. We use it to avoid having to change the old proofs below
theorem det_apply' (M : Matrix n n R) : M.det = ∑ σ : Perm n, ε σ * ∏ i, M (σ i) i := by
simp [det_apply, Units.smul_def]
theorem det_eq_detp_sub_detp (M : Matrix n n R) : M.det = M.detp 1 - M.detp (-1) := by
rw [det_apply, ← Equiv.sum_comp (Equiv.inv (Perm n)), ← ofSign_disjUnion, sum_disjUnion]
simp_rw [inv_apply, sign_inv, sub_eq_add_neg, detp, ← sum_neg_distrib]
refine congr_arg₂ (· + ·) (sum_congr rfl fun σ hσ ↦ ?_) (sum_congr rfl fun σ hσ ↦ ?_) <;>
rw [mem_ofSign.mp hσ, ← Equiv.prod_comp σ] <;> simp
@[simp]
theorem det_diagonal {d : n → R} : det (diagonal d) = ∏ i, d i := by
rw [det_apply']
refine (Finset.sum_eq_single 1 ?_ ?_).trans ?_
· rintro σ - h2
obtain ⟨x, h3⟩ := not_forall.1 (mt Equiv.ext h2)
convert mul_zero (ε σ)
apply Finset.prod_eq_zero (mem_univ x)
exact if_neg h3
· simp
· simp
theorem det_zero (_ : Nonempty n) : det (0 : Matrix n n R) = 0 :=
(detRowAlternating : (n → R) [⋀^n]→ₗ[R] R).map_zero
@[simp]
theorem det_one : det (1 : Matrix n n R) = 1 := by rw [← diagonal_one]; simp [-diagonal_one]
theorem det_isEmpty [IsEmpty n] {A : Matrix n n R} : det A = 1 := by simp [det_apply]
@[simp]
theorem coe_det_isEmpty [IsEmpty n] : (det : Matrix n n R → R) = Function.const _ 1 := by
ext
exact det_isEmpty
theorem det_eq_one_of_card_eq_zero {A : Matrix n n R} (h : Fintype.card n = 0) : det A = 1 :=
haveI : IsEmpty n := Fintype.card_eq_zero_iff.mp h
det_isEmpty
/-- If `n` has only one element, the determinant of an `n` by `n` matrix is just that element.
Although `Unique` implies `DecidableEq` and `Fintype`, the instances might
not be syntactically equal. Thus, we need to fill in the args explicitly. -/
@[simp]
theorem det_unique {n : Type*} [Unique n] [DecidableEq n] [Fintype n] (A : Matrix n n R) :
det A = A default default := by simp [det_apply, univ_unique]
theorem det_eq_elem_of_subsingleton [Subsingleton n] (A : Matrix n n R) (k : n) :
det A = A k k := by
have := uniqueOfSubsingleton k
convert det_unique A
theorem det_eq_elem_of_card_eq_one {A : Matrix n n R} (h : Fintype.card n = 1) (k : n) :
det A = A k k :=
haveI : Subsingleton n := Fintype.card_le_one_iff_subsingleton.mp h.le
det_eq_elem_of_subsingleton _ _
theorem det_mul_aux {M N : Matrix n n R} {p : n → n} (H : ¬Bijective p) :
(∑ σ : Perm n, ε σ * ∏ x, M (σ x) (p x) * N (p x) x) = 0 := by
obtain ⟨i, j, hpij, hij⟩ : ∃ i j, p i = p j ∧ i ≠ j := by
rw [← Finite.injective_iff_bijective, Injective] at H
push_neg at H
exact H
exact
sum_involution (fun σ _ => σ * Equiv.swap i j)
(fun σ _ => by
have : (∏ x, M (σ x) (p x)) = ∏ x, M ((σ * Equiv.swap i j) x) (p x) :=
Fintype.prod_equiv (swap i j) _ _ (by simp [apply_swap_eq_self hpij])
simp [this, sign_swap hij, -sign_swap', prod_mul_distrib])
(fun σ _ _ => (not_congr mul_swap_eq_iff).mpr hij) (fun _ _ => mem_univ _) fun σ _ =>
mul_swap_involutive i j σ
@[simp]
theorem det_mul (M N : Matrix n n R) : det (M * N) = det M * det N :=
calc
det (M * N) = ∑ p : n → n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
simp only [det_apply', mul_apply, prod_univ_sum, mul_sum, Fintype.piFinset_univ]
rw [Finset.sum_comm]
_ = ∑ p : n → n with Bijective p, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (p i) * N (p i) i := by
refine (sum_subset (filter_subset _ _) fun f _ hbij ↦ det_mul_aux ?_).symm
simpa only [true_and, mem_filter, mem_univ] using hbij
_ = ∑ τ : Perm n, ∑ σ : Perm n, ε σ * ∏ i, M (σ i) (τ i) * N (τ i) i :=
sum_bij (fun p h ↦ Equiv.ofBijective p (mem_filter.1 h).2) (fun _ _ ↦ mem_univ _)
(fun _ _ _ _ h ↦ by injection h)
(fun b _ ↦ ⟨b, mem_filter.2 ⟨mem_univ _, b.bijective⟩, coe_fn_injective rfl⟩) fun _ _ ↦ rfl
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * ε τ * ∏ j, M (τ j) (σ j) := by
simp only [mul_comm, mul_left_comm, prod_mul_distrib, mul_assoc]
_ = ∑ σ : Perm n, ∑ τ : Perm n, (∏ i, N (σ i) i) * (ε σ * ε τ) * ∏ i, M (τ i) i :=
(sum_congr rfl fun σ _ =>
Fintype.sum_equiv (Equiv.mulRight σ⁻¹) _ _ fun τ => by
have : (∏ j, M (τ j) (σ j)) = ∏ j, M ((τ * σ⁻¹) j) j := by
rw [← (σ⁻¹ : _ ≃ _).prod_comp]
simp only [Equiv.Perm.coe_mul, apply_inv_self, Function.comp_apply]
have h : ε σ * ε (τ * σ⁻¹) = ε τ :=
calc
ε σ * ε (τ * σ⁻¹) = ε (τ * σ⁻¹ * σ) := by
rw [mul_comm, sign_mul (τ * σ⁻¹)]
simp only [Int.cast_mul, Units.val_mul]
_ = ε τ := by simp only [inv_mul_cancel_right]
simp_rw [Equiv.coe_mulRight, h]
simp only [this])
_ = det M * det N := by
simp only [det_apply', Finset.mul_sum, mul_comm, mul_left_comm, mul_assoc]
/-- The determinant of a matrix, as a monoid homomorphism. -/
def detMonoidHom : Matrix n n R →* R where
toFun := det
map_one' := det_one
map_mul' := det_mul
@[simp]
theorem coe_detMonoidHom : (detMonoidHom : Matrix n n R → R) = det :=
rfl
/-- On square matrices, `mul_comm` applies under `det`. -/
theorem det_mul_comm (M N : Matrix m m R) : det (M * N) = det (N * M) := by
rw [det_mul, det_mul, mul_comm]
/-- On square matrices, `mul_left_comm` applies under `det`. -/
theorem det_mul_left_comm (M N P : Matrix m m R) : det (M * (N * P)) = det (N * (M * P)) := by
rw [← Matrix.mul_assoc, ← Matrix.mul_assoc, det_mul, det_mul_comm M N, ← det_mul]
/-- On square matrices, `mul_right_comm` applies under `det`. -/
theorem det_mul_right_comm (M N P : Matrix m m R) : det (M * N * P) = det (M * P * N) := by
rw [Matrix.mul_assoc, Matrix.mul_assoc, det_mul, det_mul_comm N P, ← det_mul]
-- TODO(https://github.com/leanprover-community/mathlib4/issues/6607): fix elaboration so `val` isn't needed
theorem det_units_conj (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det (M.val * N * M⁻¹.val) = det N := by
rw [det_mul_right_comm, Units.mul_inv, one_mul]
-- TODO(https://github.com/leanprover-community/mathlib4/issues/6607): fix elaboration so `val` isn't needed
theorem det_units_conj' (M : (Matrix m m R)ˣ) (N : Matrix m m R) :
det (M⁻¹.val * N * ↑M.val) = det N :=
det_units_conj M⁻¹ N
/-- Transposing a matrix preserves the determinant. -/
@[simp]
theorem det_transpose (M : Matrix n n R) : Mᵀ.det = M.det := by
rw [det_apply', det_apply']
refine Fintype.sum_bijective _ inv_involutive.bijective _ _ ?_
intro σ
rw [sign_inv]
congr 1
apply Fintype.prod_equiv σ
simp
/-- Permuting the columns changes the sign of the determinant. -/
theorem det_permute (σ : Perm n) (M : Matrix n n R) :
(M.submatrix σ id).det = Perm.sign σ * M.det :=
((detRowAlternating : (n → R) [⋀^n]→ₗ[R] R).map_perm M σ).trans (by simp [Units.smul_def])
/-- Permuting the rows changes the sign of the determinant. -/
theorem det_permute' (σ : Perm n) (M : Matrix n n R) :
(M.submatrix id σ).det = Perm.sign σ * M.det := by
rw [← det_transpose, transpose_submatrix, det_permute, det_transpose]
/-- Permuting rows and columns with the same equivalence does not change the determinant. -/
@[simp]
theorem det_submatrix_equiv_self (e : n ≃ m) (A : Matrix m m R) :
det (A.submatrix e e) = det A := by
rw [det_apply', det_apply']
apply Fintype.sum_equiv (Equiv.permCongr e)
intro σ
rw [Equiv.Perm.sign_permCongr e σ]
congr 1
apply Fintype.prod_equiv e
intro i
rw [Equiv.permCongr_apply, Equiv.symm_apply_apply, submatrix_apply]
/-- Permuting rows and columns with two equivalences does not change the absolute value of the
determinant. -/
@[simp]
theorem abs_det_submatrix_equiv_equiv {R : Type*}
[CommRing R] [LinearOrder R] [IsStrictOrderedRing R]
(e₁ e₂ : n ≃ m) (A : Matrix m m R) :
|(A.submatrix e₁ e₂).det| = |A.det| := by
have hee : e₂ = e₁.trans (e₁.symm.trans e₂) := by ext; simp
rw [hee]
show |((A.submatrix id (e₁.symm.trans e₂)).submatrix e₁ e₁).det| = |A.det|
rw [Matrix.det_submatrix_equiv_self, Matrix.det_permute', abs_mul, abs_unit_intCast, one_mul]
/-- Reindexing both indices along the same equivalence preserves the determinant.
For the `simp` version of this lemma, see `det_submatrix_equiv_self`; this one is unsuitable because
`Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem det_reindex_self (e : m ≃ n) (A : Matrix m m R) : det (reindex e e A) = det A :=
det_submatrix_equiv_self e.symm A
/-- Reindexing both indices along equivalences preserves the absolute of the determinant.
For the `simp` version of this lemma, see `abs_det_submatrix_equiv_equiv`;
this one is unsuitable because `Matrix.reindex_apply` unfolds `reindex` first.
-/
theorem abs_det_reindex {R : Type*} [CommRing R] [LinearOrder R] [IsStrictOrderedRing R]
(e₁ e₂ : m ≃ n) (A : Matrix m m R) :
|det (reindex e₁ e₂ A)| = |det A| :=
abs_det_submatrix_equiv_equiv e₁.symm e₂.symm A
theorem det_smul (A : Matrix n n R) (c : R) : det (c • A) = c ^ Fintype.card n * det A :=
calc
det (c • A) = det ((diagonal fun _ => c) * A) := by rw [smul_eq_diagonal_mul]
_ = det (diagonal fun _ => c) * det A := det_mul _ _
_ = c ^ Fintype.card n * det A := by simp
@[simp]
theorem det_smul_of_tower {α} [Monoid α] [MulAction α R] [IsScalarTower α R R]
[SMulCommClass α R R] (c : α) (A : Matrix n n R) :
det (c • A) = c ^ Fintype.card n • det A := by
rw [← smul_one_smul R c A, det_smul, smul_pow, one_pow, smul_mul_assoc, one_mul]
theorem det_neg (A : Matrix n n R) : det (-A) = (-1) ^ Fintype.card n * det A := by
rw [← det_smul, neg_one_smul]
/-- A variant of `Matrix.det_neg` with scalar multiplication by `Units ℤ` instead of multiplication
by `R`. -/
theorem det_neg_eq_smul (A : Matrix n n R) :
det (-A) = (-1 : Units ℤ) ^ Fintype.card n • det A := by
rw [← det_smul_of_tower, Units.neg_smul, one_smul]
/-- Multiplying each row by a fixed `v i` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_row (v : n → R) (A : Matrix n n R) :
det (of fun i j => v j * A i j) = (∏ i, v i) * det A :=
calc
det (of fun i j => v j * A i j) = det (A * diagonal v) :=
congr_arg det <| by
ext
simp [mul_comm]
_ = (∏ i, v i) * det A := by rw [det_mul, det_diagonal, mul_comm]
/-- Multiplying each column by a fixed `v j` multiplies the determinant by
the product of the `v`s. -/
theorem det_mul_column (v : n → R) (A : Matrix n n R) :
det (of fun i j => v i * A i j) = (∏ i, v i) * det A :=
MultilinearMap.map_smul_univ _ v A
@[simp]
theorem det_pow (M : Matrix m m R) (n : ℕ) : det (M ^ n) = det M ^ n :=
(detMonoidHom : Matrix m m R →* R).map_pow M n
section HomMap
variable {S : Type w} [CommRing S]
theorem _root_.RingHom.map_det (f : R →+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) := by
simp [Matrix.det_apply', map_sum f, map_prod f]
theorem _root_.RingEquiv.map_det (f : R ≃+* S) (M : Matrix n n R) :
f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
theorem _root_.AlgHom.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T] (f : S →ₐ[R] T)
(M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toRingHom.map_det _
theorem _root_.AlgEquiv.map_det [Algebra R S] {T : Type z} [CommRing T] [Algebra R T]
(f : S ≃ₐ[R] T) (M : Matrix n n S) : f M.det = Matrix.det (f.mapMatrix M) :=
f.toAlgHom.map_det _
@[norm_cast]
theorem _root_.Int.cast_det (M : Matrix n n ℤ) :
(M.det : R) = (M.map fun x ↦ (x : R)).det :=
Int.castRingHom R |>.map_det M
@[norm_cast]
theorem _root_.Rat.cast_det {F : Type*} [Field F] [CharZero F] (M : Matrix n n ℚ) :
(M.det : F) = (M.map fun x ↦ (x : F)).det :=
Rat.castHom F |>.map_det M
end HomMap
@[simp]
theorem det_conjTranspose [StarRing R] (M : Matrix m m R) : det Mᴴ = star (det M) :=
((starRingEnd R).map_det _).symm.trans <| congr_arg star M.det_transpose
section DetZero
/-!
### `det_zero` section
Prove that a matrix with a repeated column has determinant equal to zero.
-/
theorem det_eq_zero_of_row_eq_zero {A : Matrix n n R} (i : n) (h : ∀ j, A i j = 0) : det A = 0 :=
(detRowAlternating : (n → R) [⋀^n]→ₗ[R] R).map_coord_zero i (funext h)
theorem det_eq_zero_of_column_eq_zero {A : Matrix n n R} (j : n) (h : ∀ i, A i j = 0) :
det A = 0 := by
rw [← det_transpose]
exact det_eq_zero_of_row_eq_zero j h
variable {M : Matrix n n R} {i j : n}
/-- If a matrix has a repeated row, the determinant will be zero. -/
theorem det_zero_of_row_eq (i_ne_j : i ≠ j) (hij : M i = M j) : M.det = 0 :=
(detRowAlternating : (n → R) [⋀^n]→ₗ[R] R).map_eq_zero_of_eq M hij i_ne_j
/-- If a matrix has a repeated column, the determinant will be zero. -/
theorem det_zero_of_column_eq (i_ne_j : i ≠ j) (hij : ∀ k, M k i = M k j) : M.det = 0 := by
rw [← det_transpose, det_zero_of_row_eq i_ne_j]
exact funext hij
/-- If we repeat a row of a matrix, we get a matrix of determinant zero. -/
theorem det_updateRow_eq_zero (h : i ≠ j) :
(M.updateRow j (M i)).det = 0 := det_zero_of_row_eq h (by simp [h])
/-- If we repeat a column of a matrix, we get a matrix of determinant zero. -/
theorem det_updateCol_eq_zero (h : i ≠ j) :
(M.updateCol j (fun k ↦ M k i)).det = 0 := det_zero_of_column_eq h (by simp [h])
@[deprecated (since := "2024-12-11")] alias det_updateColumn_eq_zero := det_updateCol_eq_zero
end DetZero
theorem det_updateRow_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateRow M j <| u + v) = det (updateRow M j u) + det (updateRow M j v) :=
(detRowAlternating : (n → R) [⋀^n]→ₗ[R] R).map_update_add M j u v
| Mathlib/LinearAlgebra/Matrix/Determinant/Basic.lean | 384 | 385 | theorem det_updateCol_add (M : Matrix n n R) (j : n) (u v : n → R) :
det (updateCol M j <| u + v) = det (updateCol M j u) + det (updateCol M j v) := by | |
/-
Copyright (c) 2020 Robert Y. Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Robert Y. Lewis
-/
import Batteries.Tactic.Lint.Basic
import Mathlib.Algebra.Order.Monoid.Unbundled.Basic
import Mathlib.Algebra.Order.Ring.Defs
import Mathlib.Algebra.Order.ZeroLEOne
import Mathlib.Data.Nat.Cast.Order.Ring
import Mathlib.Data.Int.Order.Basic
import Mathlib.Data.Ineq
/-!
# Lemmas for `linarith`.
Those in the `Linarith` namespace should stay here.
Those outside the `Linarith` namespace may be deleted as they are ported to mathlib4.
-/
namespace Linarith
universe u
theorem lt_irrefl {α : Type u} [Preorder α] {a : α} : ¬a < a := _root_.lt_irrefl a
theorem eq_of_eq_of_eq {α} [Semiring α] {a b : α} (ha : a = 0) (hb : b = 0) : a + b = 0 := by
simp [*]
section Semiring
variable {α : Type u} [Semiring α] [PartialOrder α]
theorem zero_lt_one [IsStrictOrderedRing α] : (0:α) < 1 :=
_root_.zero_lt_one
theorem le_of_eq_of_le {a b : α} (ha : a = 0) (hb : b ≤ 0) : a + b ≤ 0 := by
simp [*]
| Mathlib/Tactic/Linarith/Lemmas.lean | 39 | 40 | theorem lt_of_eq_of_lt {a b : α} (ha : a = 0) (hb : b < 0) : a + b < 0 := by | simp [*] |
/-
Copyright (c) 2019 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison, Simon Hudon
-/
import Mathlib.CategoryTheory.Monoidal.Category
import Mathlib.CategoryTheory.Limits.Shapes.BinaryProducts
import Mathlib.CategoryTheory.PEmpty
/-!
# The monoidal structure on a category with chosen finite products.
This is a variant of the development in `CategoryTheory.Monoidal.OfHasFiniteProducts`,
which uses specified choices of the terminal object and binary product,
enabling the construction of a cartesian category with specific definitions of the tensor unit
and tensor product.
(Because the construction in `CategoryTheory.Monoidal.OfHasFiniteProducts` uses `HasLimit`
classes, the actual definitions there are opaque behind `Classical.choice`.)
We use this in `CategoryTheory.Monoidal.TypeCat` to construct the monoidal category of types
so that the tensor product is the usual cartesian product of types.
For now we only do the construction from products, and not from coproducts,
which seems less often useful.
-/
universe v u
namespace CategoryTheory
variable (C : Type u) [Category.{v} C] {X Y : C}
namespace Limits
section
variable {C}
/-- Swap the two sides of a `BinaryFan`. -/
def BinaryFan.swap {P Q : C} (t : BinaryFan P Q) : BinaryFan Q P :=
BinaryFan.mk t.snd t.fst
@[simp]
theorem BinaryFan.swap_fst {P Q : C} (t : BinaryFan P Q) : t.swap.fst = t.snd :=
rfl
@[simp]
theorem BinaryFan.swap_snd {P Q : C} (t : BinaryFan P Q) : t.swap.snd = t.fst :=
rfl
/-- If a binary fan `t` over `P Q` is a limit cone, then `t.swap` is a limit cone over `Q P`.
-/
@[simps]
def IsLimit.swapBinaryFan {P Q : C} {t : BinaryFan P Q} (I : IsLimit t) : IsLimit t.swap where
lift s := I.lift (BinaryFan.swap s)
fac s := by rintro ⟨⟨⟩⟩ <;> simp
uniq s m w := by
have h := I.uniq (BinaryFan.swap s) m
rw [h]
rintro ⟨j⟩
specialize w ⟨WalkingPair.swap j⟩
cases j <;> exact w
/-- Construct `HasBinaryProduct Q P` from `HasBinaryProduct P Q`.
This can't be an instance, as it would cause a loop in typeclass search.
-/
theorem HasBinaryProduct.swap (P Q : C) [HasBinaryProduct P Q] : HasBinaryProduct Q P :=
HasLimit.mk ⟨BinaryFan.swap (limit.cone (pair P Q)), (limit.isLimit (pair P Q)).swapBinaryFan⟩
/-- Given a limit cone over `X` and `Y`, and another limit cone over `Y` and `X`, we can construct
an isomorphism between the cone points. Relative to some fixed choice of limits cones for every
pair, these isomorphisms constitute a braiding.
-/
def BinaryFan.braiding {X Y : C} {s : BinaryFan X Y} (P : IsLimit s) {t : BinaryFan Y X}
(Q : IsLimit t) : s.pt ≅ t.pt :=
IsLimit.conePointUniqueUpToIso P Q.swapBinaryFan
section
variable {X Y : C} {s : BinaryFan X Y} (P : IsLimit s) {t : BinaryFan Y X} (Q : IsLimit t)
@[reassoc (attr := simp)]
theorem BinaryFan.braiding_hom_fst : (braiding P Q).hom ≫ t.fst = s.snd :=
IsLimit.conePointUniqueUpToIso_hom_comp P _ ⟨WalkingPair.right⟩
@[reassoc (attr := simp)]
theorem BinaryFan.braiding_hom_snd : (braiding P Q).hom ≫ t.snd = s.fst :=
IsLimit.conePointUniqueUpToIso_hom_comp P _ ⟨WalkingPair.left⟩
@[reassoc (attr := simp)]
theorem BinaryFan.braiding_inv_fst : (braiding P Q).inv ≫ s.fst = t.snd :=
IsLimit.conePointUniqueUpToIso_inv_comp P _ ⟨WalkingPair.left⟩
@[reassoc (attr := simp)]
theorem BinaryFan.braiding_inv_snd : (braiding P Q).inv ≫ s.snd = t.fst :=
IsLimit.conePointUniqueUpToIso_inv_comp P _ ⟨WalkingPair.right⟩
end
/-- Given binary fans `sXY` over `X Y`, and `sYZ` over `Y Z`, and `s` over `sXY.X Z`,
if `sYZ` is a limit cone we can construct a binary fan over `X sYZ.X`.
This is an ingredient of building the associator for a cartesian category.
-/
def BinaryFan.assoc {X Y Z : C} {sXY : BinaryFan X Y} {sYZ : BinaryFan Y Z} (Q : IsLimit sYZ)
(s : BinaryFan sXY.pt Z) : BinaryFan X sYZ.pt :=
BinaryFan.mk (s.fst ≫ sXY.fst) (Q.lift (BinaryFan.mk (s.fst ≫ sXY.snd) s.snd))
@[simp]
theorem BinaryFan.assoc_fst {X Y Z : C} {sXY : BinaryFan X Y} {sYZ : BinaryFan Y Z}
(Q : IsLimit sYZ) (s : BinaryFan sXY.pt Z) : (BinaryFan.assoc Q s).fst = s.fst ≫ sXY.fst :=
rfl
@[simp]
theorem BinaryFan.assoc_snd {X Y Z : C} {sXY : BinaryFan X Y} {sYZ : BinaryFan Y Z}
(Q : IsLimit sYZ) (s : BinaryFan sXY.pt Z) :
(BinaryFan.assoc Q s).snd = Q.lift (BinaryFan.mk (s.fst ≫ sXY.snd) s.snd) :=
rfl
/-- Given binary fans `sXY` over `X Y`, and `sYZ` over `Y Z`, and `s` over `X sYZ.X`,
if `sYZ` is a limit cone we can construct a binary fan over `sXY.X Z`.
This is an ingredient of building the associator for a cartesian category.
-/
def BinaryFan.assocInv {X Y Z : C} {sXY : BinaryFan X Y} (P : IsLimit sXY) {sYZ : BinaryFan Y Z}
(s : BinaryFan X sYZ.pt) : BinaryFan sXY.pt Z :=
BinaryFan.mk (P.lift (BinaryFan.mk s.fst (s.snd ≫ sYZ.fst))) (s.snd ≫ sYZ.snd)
@[simp]
theorem BinaryFan.assocInv_fst {X Y Z : C} {sXY : BinaryFan X Y} (P : IsLimit sXY)
{sYZ : BinaryFan Y Z} (s : BinaryFan X sYZ.pt) :
(BinaryFan.assocInv P s).fst = P.lift (BinaryFan.mk s.fst (s.snd ≫ sYZ.fst)) :=
rfl
@[simp]
theorem BinaryFan.assocInv_snd {X Y Z : C} {sXY : BinaryFan X Y} (P : IsLimit sXY)
{sYZ : BinaryFan Y Z} (s : BinaryFan X sYZ.pt) :
(BinaryFan.assocInv P s).snd = s.snd ≫ sYZ.snd :=
rfl
/-- If all the binary fans involved a limit cones, `BinaryFan.assoc` produces another limit cone.
-/
@[simps]
def IsLimit.assoc {X Y Z : C} {sXY : BinaryFan X Y} (P : IsLimit sXY) {sYZ : BinaryFan Y Z}
(Q : IsLimit sYZ) {s : BinaryFan sXY.pt Z} (R : IsLimit s) : IsLimit (BinaryFan.assoc Q s) where
lift t := R.lift (BinaryFan.assocInv P t)
fac t := by
rintro ⟨⟨⟩⟩ <;> simp
apply Q.hom_ext
rintro ⟨⟨⟩⟩ <;> simp
uniq t m w := by
have h := R.uniq (BinaryFan.assocInv P t) m
rw [h]
rintro ⟨⟨⟩⟩ <;> simp
· apply P.hom_ext
rintro ⟨⟨⟩⟩ <;> simp
· exact w ⟨WalkingPair.left⟩
· specialize w ⟨WalkingPair.right⟩
simp? at w says
simp only [pair_obj_right, BinaryFan.π_app_right, BinaryFan.assoc_snd,
Functor.const_obj_obj, pair_obj_left] at w
rw [← w]
simp
· specialize w ⟨WalkingPair.right⟩
simp? at w says
simp only [pair_obj_right, BinaryFan.π_app_right, BinaryFan.assoc_snd,
Functor.const_obj_obj, pair_obj_left] at w
rw [← w]
simp
/-- Given two pairs of limit cones corresponding to the parenthesisations of `X × Y × Z`,
we obtain an isomorphism between the cone points.
-/
abbrev BinaryFan.associator {X Y Z : C} {sXY : BinaryFan X Y} (P : IsLimit sXY)
{sYZ : BinaryFan Y Z} (Q : IsLimit sYZ) {s : BinaryFan sXY.pt Z} (R : IsLimit s)
{t : BinaryFan X sYZ.pt} (S : IsLimit t) : s.pt ≅ t.pt :=
IsLimit.conePointUniqueUpToIso (IsLimit.assoc P Q R) S
/-- Given a fixed family of limit data for every pair `X Y`, we obtain an associator.
-/
abbrev BinaryFan.associatorOfLimitCone (L : ∀ X Y : C, LimitCone (pair X Y)) (X Y Z : C) :
(L (L X Y).cone.pt Z).cone.pt ≅ (L X (L Y Z).cone.pt).cone.pt :=
BinaryFan.associator (L X Y).isLimit (L Y Z).isLimit (L (L X Y).cone.pt Z).isLimit
(L X (L Y Z).cone.pt).isLimit
/-- Construct a left unitor from specified limit cones.
-/
@[simps]
def BinaryFan.leftUnitor {X : C} {s : Cone (Functor.empty.{0} C)} (P : IsLimit s)
{t : BinaryFan s.pt X} (Q : IsLimit t) : t.pt ≅ X where
hom := t.snd
inv := Q.lift <| BinaryFan.mk (P.lift ⟨_, fun x => x.as.elim, fun {x} => x.as.elim⟩) (𝟙 _)
hom_inv_id := by
apply Q.hom_ext
rintro ⟨⟨⟩⟩
· apply P.hom_ext
rintro ⟨⟨⟩⟩
· simp
/-- Construct a right unitor from specified limit cones.
-/
@[simps]
def BinaryFan.rightUnitor {X : C} {s : Cone (Functor.empty.{0} C)} (P : IsLimit s)
{t : BinaryFan X s.pt} (Q : IsLimit t) : t.pt ≅ X where
hom := t.fst
inv := Q.lift <| BinaryFan.mk (𝟙 _) <| P.lift ⟨_, fun x => x.as.elim, fun {x} => x.as.elim⟩
hom_inv_id := by
apply Q.hom_ext
rintro ⟨⟨⟩⟩
· simp
· apply P.hom_ext
rintro ⟨⟨⟩⟩
end
end Limits
open CategoryTheory.Limits
section
-- Porting note: no tidy
-- attribute [local tidy] tactic.case_bash
variable {C}
variable (𝒯 : LimitCone (Functor.empty.{0} C))
variable (ℬ : ∀ X Y : C, LimitCone (pair X Y))
namespace MonoidalOfChosenFiniteProducts
/-- Implementation of the tensor product for `MonoidalOfChosenFiniteProducts`. -/
abbrev tensorObj (X Y : C) : C :=
(ℬ X Y).cone.pt
/-- Implementation of the tensor product of morphisms for `MonoidalOfChosenFiniteProducts`. -/
abbrev tensorHom {W X Y Z : C} (f : W ⟶ X) (g : Y ⟶ Z) : tensorObj ℬ W Y ⟶ tensorObj ℬ X Z :=
(BinaryFan.IsLimit.lift' (ℬ X Z).isLimit ((ℬ W Y).cone.π.app ⟨WalkingPair.left⟩ ≫ f)
(((ℬ W Y).cone.π.app ⟨WalkingPair.right⟩ : (ℬ W Y).cone.pt ⟶ Y) ≫ g)).val
theorem tensor_id (X₁ X₂ : C) : tensorHom ℬ (𝟙 X₁) (𝟙 X₂) = 𝟙 (tensorObj ℬ X₁ X₂) := by
apply IsLimit.hom_ext (ℬ _ _).isLimit
rintro ⟨⟨⟩⟩ <;>
· dsimp [tensorHom]
simp
| Mathlib/CategoryTheory/Monoidal/OfChosenFiniteProducts/Basic.lean | 249 | 254 | theorem tensor_comp {X₁ Y₁ Z₁ X₂ Y₂ Z₂ : C} (f₁ : X₁ ⟶ Y₁) (f₂ : X₂ ⟶ Y₂) (g₁ : Y₁ ⟶ Z₁)
(g₂ : Y₂ ⟶ Z₂) : tensorHom ℬ (f₁ ≫ g₁) (f₂ ≫ g₂) = tensorHom ℬ f₁ f₂ ≫ tensorHom ℬ g₁ g₂ := by | apply IsLimit.hom_ext (ℬ _ _).isLimit
rintro ⟨⟨⟩⟩ <;>
· dsimp [tensorHom]
simp |
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Yaël Dillies
-/
import Mathlib.MeasureTheory.Integral.Bochner.ContinuousLinearMap
/-!
# Integral average of a function
In this file we define `MeasureTheory.average μ f` (notation: `⨍ x, f x ∂μ`) to be the average
value of `f` with respect to measure `μ`. It is defined as `∫ x, f x ∂((μ univ)⁻¹ • μ)`, so it
is equal to zero if `f` is not integrable or if `μ` is an infinite measure. If `μ` is a probability
measure, then the average of any function is equal to its integral.
For the average on a set, we use `⨍ x in s, f x ∂μ` (notation for `⨍ x, f x ∂(μ.restrict s)`). For
average w.r.t. the volume, one can omit `∂volume`.
Both have a version for the Lebesgue integral rather than Bochner.
We prove several version of the first moment method: An integrable function is below/above its
average on a set of positive measure:
* `measure_le_setLAverage_pos` for the Lebesgue integral
* `measure_le_setAverage_pos` for the Bochner integral
## Implementation notes
The average is defined as an integral over `(μ univ)⁻¹ • μ` so that all theorems about Bochner
integrals work for the average without modifications. For theorems that require integrability of a
function, we provide a convenience lemma `MeasureTheory.Integrable.to_average`.
## Tags
integral, center mass, average value
-/
open ENNReal MeasureTheory MeasureTheory.Measure Metric Set Filter TopologicalSpace Function
open scoped Topology ENNReal Convex
variable {α E F : Type*} {m0 : MeasurableSpace α} [NormedAddCommGroup E] [NormedSpace ℝ E]
[NormedAddCommGroup F] [NormedSpace ℝ F] [CompleteSpace F] {μ ν : Measure α}
{s t : Set α}
/-!
### Average value of a function w.r.t. a measure
The (Bochner, Lebesgue) average value of a function `f` w.r.t. a measure `μ` (notation:
`⨍ x, f x ∂μ`, `⨍⁻ x, f x ∂μ`) is defined as the (Bochner, Lebesgue) integral divided by the total
measure, so it is equal to zero if `μ` is an infinite measure, and (typically) equal to infinity if
`f` is not integrable. If `μ` is a probability measure, then the average of any function is equal to
its integral.
-/
namespace MeasureTheory
section ENNReal
variable (μ) {f g : α → ℝ≥0∞}
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ`, denoted `⨍⁻ x, f x ∂μ`.
It is equal to `(μ univ)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `μ` is an infinite measure. If
`μ` is a probability measure, then the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x ∂μ`, defined as `⨍⁻ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
noncomputable def laverage (f : α → ℝ≥0∞) := ∫⁻ x, f x ∂(μ univ)⁻¹ • μ
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ`.
It is equal to `(μ univ)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `μ` is an infinite measure. If
`μ` is a probability measure, then the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x ∂μ`, defined as `⨍⁻ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍⁻ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => laverage μ r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. to the standard measure.
It is equal to `(volume univ)⁻¹ * ∫⁻ x, f x`, so it takes value zero if the space has infinite
measure. In a probability space, the average of any function is equal to its integral.
For the average on a set, use `⨍⁻ x in s, f x`, defined as `⨍⁻ x, f x ∂(volume.restrict s)`. -/
notation3 "⨍⁻ "(...)", "r:60:(scoped f => laverage volume f) => r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. a measure `μ` on a set `s`.
It is equal to `(μ s)⁻¹ * ∫⁻ x, f x ∂μ`, so it takes value zero if `s` has infinite measure. If `s`
has measure `1`, then the average of any function is equal to its integral.
For the average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍⁻ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => laverage (Measure.restrict μ s) r
/-- Average value of an `ℝ≥0∞`-valued function `f` w.r.t. to the standard measure on a set `s`.
It is equal to `(volume s)⁻¹ * ∫⁻ x, f x`, so it takes value zero if `s` has infinite measure. If
`s` has measure `1`, then the average of any function is equal to its integral. -/
notation3 (prettyPrint := false)
"⨍⁻ "(...)" in "s", "r:60:(scoped f => laverage Measure.restrict volume s f) => r
@[simp]
theorem laverage_zero : ⨍⁻ _x, (0 : ℝ≥0∞) ∂μ = 0 := by rw [laverage, lintegral_zero]
@[simp]
theorem laverage_zero_measure (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂(0 : Measure α) = 0 := by simp [laverage]
theorem laverage_eq' (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂(μ univ)⁻¹ • μ := rfl
theorem laverage_eq (f : α → ℝ≥0∞) : ⨍⁻ x, f x ∂μ = (∫⁻ x, f x ∂μ) / μ univ := by
rw [laverage_eq', lintegral_smul_measure, ENNReal.div_eq_inv_mul, smul_eq_mul]
theorem laverage_eq_lintegral [IsProbabilityMeasure μ] (f : α → ℝ≥0∞) :
⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂μ := by rw [laverage, measure_univ, inv_one, one_smul]
@[simp]
theorem measure_mul_laverage [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
μ univ * ⨍⁻ x, f x ∂μ = ∫⁻ x, f x ∂μ := by
rcases eq_or_ne μ 0 with hμ | hμ
· rw [hμ, lintegral_zero_measure, laverage_zero_measure, mul_zero]
· rw [laverage_eq, ENNReal.mul_div_cancel (measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)]
theorem setLAverage_eq (f : α → ℝ≥0∞) (s : Set α) :
⨍⁻ x in s, f x ∂μ = (∫⁻ x in s, f x ∂μ) / μ s := by rw [laverage_eq, restrict_apply_univ]
@[deprecated (since := "2025-04-22")] alias setLaverage_eq := setLAverage_eq
theorem setLAverage_eq' (f : α → ℝ≥0∞) (s : Set α) :
⨍⁻ x in s, f x ∂μ = ∫⁻ x, f x ∂(μ s)⁻¹ • μ.restrict s := by
simp only [laverage_eq', restrict_apply_univ]
@[deprecated (since := "2025-04-22")] alias setLaverage_eq' := setLAverage_eq'
variable {μ}
theorem laverage_congr {f g : α → ℝ≥0∞} (h : f =ᵐ[μ] g) : ⨍⁻ x, f x ∂μ = ⨍⁻ x, g x ∂μ := by
simp only [laverage_eq, lintegral_congr_ae h]
theorem setLAverage_congr (h : s =ᵐ[μ] t) : ⨍⁻ x in s, f x ∂μ = ⨍⁻ x in t, f x ∂μ := by
simp only [setLAverage_eq, setLIntegral_congr h, measure_congr h]
@[deprecated (since := "2025-04-22")] alias setLaverage_congr := setLAverage_congr
theorem setLAverage_congr_fun (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
⨍⁻ x in s, f x ∂μ = ⨍⁻ x in s, g x ∂μ := by
simp only [laverage_eq, setLIntegral_congr_fun hs h]
@[deprecated (since := "2025-04-22")] alias setLaverage_congr_fun := setLAverage_congr_fun
theorem laverage_lt_top (hf : ∫⁻ x, f x ∂μ ≠ ∞) : ⨍⁻ x, f x ∂μ < ∞ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [laverage_eq]
exact div_lt_top hf (measure_univ_ne_zero.2 hμ)
theorem setLAverage_lt_top : ∫⁻ x in s, f x ∂μ ≠ ∞ → ⨍⁻ x in s, f x ∂μ < ∞ :=
laverage_lt_top
@[deprecated (since := "2025-04-22")] alias setLaverage_lt_top := setLAverage_lt_top
theorem laverage_add_measure :
⨍⁻ x, f x ∂(μ + ν) =
μ univ / (μ univ + ν univ) * ⨍⁻ x, f x ∂μ + ν univ / (μ univ + ν univ) * ⨍⁻ x, f x ∂ν := by
by_cases hμ : IsFiniteMeasure μ; swap
· rw [not_isFiniteMeasure_iff] at hμ
simp [laverage_eq, hμ]
by_cases hν : IsFiniteMeasure ν; swap
· rw [not_isFiniteMeasure_iff] at hν
simp [laverage_eq, hν]
haveI := hμ; haveI := hν
simp only [← ENNReal.mul_div_right_comm, measure_mul_laverage, ← ENNReal.add_div,
← lintegral_add_measure, ← Measure.add_apply, ← laverage_eq]
theorem measure_mul_setLAverage (f : α → ℝ≥0∞) (h : μ s ≠ ∞) :
μ s * ⨍⁻ x in s, f x ∂μ = ∫⁻ x in s, f x ∂μ := by
have := Fact.mk h.lt_top
rw [← measure_mul_laverage, restrict_apply_univ]
@[deprecated (since := "2025-04-22")] alias measure_mul_setLaverage := measure_mul_setLAverage
theorem laverage_union (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ) :
⨍⁻ x in s ∪ t, f x ∂μ =
μ s / (μ s + μ t) * ⨍⁻ x in s, f x ∂μ + μ t / (μ s + μ t) * ⨍⁻ x in t, f x ∂μ := by
rw [restrict_union₀ hd ht, laverage_add_measure, restrict_apply_univ, restrict_apply_univ]
theorem laverage_union_mem_openSegment (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hs₀ : μ s ≠ 0) (ht₀ : μ t ≠ 0) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) :
⨍⁻ x in s ∪ t, f x ∂μ ∈ openSegment ℝ≥0∞ (⨍⁻ x in s, f x ∂μ) (⨍⁻ x in t, f x ∂μ) := by
refine
⟨μ s / (μ s + μ t), μ t / (μ s + μ t), ENNReal.div_pos hs₀ <| add_ne_top.2 ⟨hsμ, htμ⟩,
ENNReal.div_pos ht₀ <| add_ne_top.2 ⟨hsμ, htμ⟩, ?_, (laverage_union hd ht).symm⟩
rw [← ENNReal.add_div,
ENNReal.div_self (add_eq_zero.not.2 fun h => hs₀ h.1) (add_ne_top.2 ⟨hsμ, htμ⟩)]
theorem laverage_union_mem_segment (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) :
⨍⁻ x in s ∪ t, f x ∂μ ∈ [⨍⁻ x in s, f x ∂μ -[ℝ≥0∞] ⨍⁻ x in t, f x ∂μ] := by
by_cases hs₀ : μ s = 0
· rw [← ae_eq_empty] at hs₀
rw [restrict_congr_set (hs₀.union EventuallyEq.rfl), empty_union]
exact right_mem_segment _ _ _
· refine
⟨μ s / (μ s + μ t), μ t / (μ s + μ t), zero_le _, zero_le _, ?_, (laverage_union hd ht).symm⟩
rw [← ENNReal.add_div,
ENNReal.div_self (add_eq_zero.not.2 fun h => hs₀ h.1) (add_ne_top.2 ⟨hsμ, htμ⟩)]
theorem laverage_mem_openSegment_compl_self [IsFiniteMeasure μ] (hs : NullMeasurableSet s μ)
(hs₀ : μ s ≠ 0) (hsc₀ : μ sᶜ ≠ 0) :
⨍⁻ x, f x ∂μ ∈ openSegment ℝ≥0∞ (⨍⁻ x in s, f x ∂μ) (⨍⁻ x in sᶜ, f x ∂μ) := by
simpa only [union_compl_self, restrict_univ] using
laverage_union_mem_openSegment aedisjoint_compl_right hs.compl hs₀ hsc₀ (measure_ne_top _ _)
(measure_ne_top _ _)
@[simp]
theorem laverage_const (μ : Measure α) [IsFiniteMeasure μ] [h : NeZero μ] (c : ℝ≥0∞) :
⨍⁻ _x, c ∂μ = c := by
simp only [laverage, lintegral_const, measure_univ, mul_one]
theorem setLAverage_const (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) (c : ℝ≥0∞) : ⨍⁻ _x in s, c ∂μ = c := by
simp only [setLAverage_eq, lintegral_const, Measure.restrict_apply, MeasurableSet.univ,
univ_inter, div_eq_mul_inv, mul_assoc, ENNReal.mul_inv_cancel hs₀ hs, mul_one]
@[deprecated (since := "2025-04-22")] alias setLaverage_const := setLAverage_const
theorem laverage_one [IsFiniteMeasure μ] [NeZero μ] : ⨍⁻ _x, (1 : ℝ≥0∞) ∂μ = 1 :=
laverage_const _ _
theorem setLAverage_one (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) : ⨍⁻ _x in s, (1 : ℝ≥0∞) ∂μ = 1 :=
setLAverage_const hs₀ hs _
@[deprecated (since := "2025-04-22")] alias setLaverage_one := setLAverage_one
@[simp]
theorem laverage_mul_measure_univ (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
(⨍⁻ (a : α), f a ∂μ) * μ univ = ∫⁻ x, f x ∂μ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [laverage_eq, ENNReal.div_mul_cancel (measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)]
theorem lintegral_laverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) :
∫⁻ _x, ⨍⁻ a, f a ∂μ ∂μ = ∫⁻ x, f x ∂μ := by
simp
theorem setLIntegral_setLAverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → ℝ≥0∞) (s : Set α) :
∫⁻ _x in s, ⨍⁻ a in s, f a ∂μ ∂μ = ∫⁻ x in s, f x ∂μ :=
lintegral_laverage _ _
@[deprecated (since := "2025-04-22")] alias setLintegral_setLaverage := setLIntegral_setLAverage
end ENNReal
section NormedAddCommGroup
variable (μ)
variable {f g : α → E}
/-- Average value of a function `f` w.r.t. a measure `μ`, denoted `⨍ x, f x ∂μ`.
It is equal to `(μ.real univ)⁻¹ • ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable or
if `μ` is an infinite measure. If `μ` is a probability measure, then the average of any function is
equal to its integral.
For the average on a set, use `⨍ x in s, f x ∂μ`, defined as `⨍ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
noncomputable def average (f : α → E) :=
∫ x, f x ∂(μ univ)⁻¹ • μ
/-- Average value of a function `f` w.r.t. a measure `μ`.
It is equal to `(μ.real univ)⁻¹ • ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable or
if `μ` is an infinite measure. If `μ` is a probability measure, then the average of any function is
equal to its integral.
For the average on a set, use `⨍ x in s, f x ∂μ`, defined as `⨍ x, f x ∂(μ.restrict s)`. For the
average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => average μ r
/-- Average value of a function `f` w.r.t. to the standard measure.
It is equal to `(volume.real univ)⁻¹ * ∫ x, f x`, so it takes value zero if `f` is not integrable
or if the space has infinite measure. In a probability space, the average of any function is equal
to its integral.
For the average on a set, use `⨍ x in s, f x`, defined as `⨍ x, f x ∂(volume.restrict s)`. -/
notation3 "⨍ "(...)", "r:60:(scoped f => average volume f) => r
/-- Average value of a function `f` w.r.t. a measure `μ` on a set `s`.
It is equal to `(μ.real s)⁻¹ * ∫ x, f x ∂μ`, so it takes value zero if `f` is not integrable on
`s` or if `s` has infinite measure. If `s` has measure `1`, then the average of any function is
equal to its integral.
For the average w.r.t. the volume, one can omit `∂volume`. -/
notation3 "⨍ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => average (Measure.restrict μ s) r
/-- Average value of a function `f` w.r.t. to the standard measure on a set `s`.
It is equal to `(volume.real s)⁻¹ * ∫ x, f x`, so it takes value zero `f` is not integrable on `s`
or if `s` has infinite measure. If `s` has measure `1`, then the average of any function is equal to
its integral. -/
notation3 "⨍ "(...)" in "s", "r:60:(scoped f => average (Measure.restrict volume s) f) => r
@[simp]
theorem average_zero : ⨍ _, (0 : E) ∂μ = 0 := by rw [average, integral_zero]
@[simp]
theorem average_zero_measure (f : α → E) : ⨍ x, f x ∂(0 : Measure α) = 0 := by
rw [average, smul_zero, integral_zero_measure]
@[simp]
theorem average_neg (f : α → E) : ⨍ x, -f x ∂μ = -⨍ x, f x ∂μ :=
integral_neg f
theorem average_eq' (f : α → E) : ⨍ x, f x ∂μ = ∫ x, f x ∂(μ univ)⁻¹ • μ :=
rfl
theorem average_eq (f : α → E) : ⨍ x, f x ∂μ = (μ.real univ)⁻¹ • ∫ x, f x ∂μ := by
rw [average_eq', integral_smul_measure, ENNReal.toReal_inv, measureReal_def]
theorem average_eq_integral [IsProbabilityMeasure μ] (f : α → E) : ⨍ x, f x ∂μ = ∫ x, f x ∂μ := by
rw [average, measure_univ, inv_one, one_smul]
@[simp]
theorem measure_smul_average [IsFiniteMeasure μ] (f : α → E) :
μ.real univ • ⨍ x, f x ∂μ = ∫ x, f x ∂μ := by
rcases eq_or_ne μ 0 with hμ | hμ
· rw [hμ, integral_zero_measure, average_zero_measure, smul_zero]
· rw [average_eq, smul_inv_smul₀]
refine (ENNReal.toReal_pos ?_ <| measure_ne_top _ _).ne'
rwa [Ne, measure_univ_eq_zero]
theorem setAverage_eq (f : α → E) (s : Set α) :
⨍ x in s, f x ∂μ = (μ.real s)⁻¹ • ∫ x in s, f x ∂μ := by
rw [average_eq, measureReal_restrict_apply_univ]
theorem setAverage_eq' (f : α → E) (s : Set α) :
⨍ x in s, f x ∂μ = ∫ x, f x ∂(μ s)⁻¹ • μ.restrict s := by
simp only [average_eq', restrict_apply_univ]
variable {μ}
theorem average_congr {f g : α → E} (h : f =ᵐ[μ] g) : ⨍ x, f x ∂μ = ⨍ x, g x ∂μ := by
simp only [average_eq, integral_congr_ae h]
theorem setAverage_congr (h : s =ᵐ[μ] t) : ⨍ x in s, f x ∂μ = ⨍ x in t, f x ∂μ := by
simp only [setAverage_eq, setIntegral_congr_set h, measureReal_congr h]
theorem setAverage_congr_fun (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
⨍ x in s, f x ∂μ = ⨍ x in s, g x ∂μ := by simp only [average_eq, setIntegral_congr_ae hs h]
theorem average_add_measure [IsFiniteMeasure μ] {ν : Measure α} [IsFiniteMeasure ν] {f : α → E}
(hμ : Integrable f μ) (hν : Integrable f ν) :
⨍ x, f x ∂(μ + ν) =
(μ.real univ / (μ.real univ + ν.real univ)) • ⨍ x, f x ∂μ +
(ν.real univ / (μ.real univ + ν.real univ)) • ⨍ x, f x ∂ν := by
simp only [div_eq_inv_mul, mul_smul, measure_smul_average, ← smul_add,
← integral_add_measure hμ hν, ← ENNReal.toReal_add (measure_ne_top μ _) (measure_ne_top ν _)]
rw [average_eq, measureReal_add_apply]
theorem average_pair [CompleteSpace E]
{f : α → E} {g : α → F} (hfi : Integrable f μ) (hgi : Integrable g μ) :
⨍ x, (f x, g x) ∂μ = (⨍ x, f x ∂μ, ⨍ x, g x ∂μ) :=
integral_pair hfi.to_average hgi.to_average
theorem measure_smul_setAverage (f : α → E) {s : Set α} (h : μ s ≠ ∞) :
μ.real s • ⨍ x in s, f x ∂μ = ∫ x in s, f x ∂μ := by
haveI := Fact.mk h.lt_top
rw [← measure_smul_average, measureReal_restrict_apply_univ]
theorem average_union {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) (hfs : IntegrableOn f s μ) (hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ =
(μ.real s / (μ.real s + μ.real t)) • ⨍ x in s, f x ∂μ +
(μ.real t / (μ.real s + μ.real t)) • ⨍ x in t, f x ∂μ := by
haveI := Fact.mk hsμ.lt_top; haveI := Fact.mk htμ.lt_top
rw [restrict_union₀ hd ht, average_add_measure hfs hft, measureReal_restrict_apply_univ,
measureReal_restrict_apply_univ]
theorem average_union_mem_openSegment {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t)
(ht : NullMeasurableSet t μ) (hs₀ : μ s ≠ 0) (ht₀ : μ t ≠ 0) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞)
(hfs : IntegrableOn f s μ) (hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ ∈ openSegment ℝ (⨍ x in s, f x ∂μ) (⨍ x in t, f x ∂μ) := by
replace hs₀ : 0 < μ.real s := ENNReal.toReal_pos hs₀ hsμ
replace ht₀ : 0 < μ.real t := ENNReal.toReal_pos ht₀ htμ
exact mem_openSegment_iff_div.mpr
⟨μ.real s, μ.real t, hs₀, ht₀, (average_union hd ht hsμ htμ hfs hft).symm⟩
theorem average_union_mem_segment {f : α → E} {s t : Set α} (hd : AEDisjoint μ s t)
(ht : NullMeasurableSet t μ) (hsμ : μ s ≠ ∞) (htμ : μ t ≠ ∞) (hfs : IntegrableOn f s μ)
(hft : IntegrableOn f t μ) :
⨍ x in s ∪ t, f x ∂μ ∈ [⨍ x in s, f x ∂μ -[ℝ] ⨍ x in t, f x ∂μ] := by
by_cases hse : μ s = 0
· rw [← ae_eq_empty] at hse
rw [restrict_congr_set (hse.union EventuallyEq.rfl), empty_union]
exact right_mem_segment _ _ _
· refine
mem_segment_iff_div.mpr
⟨μ.real s, μ.real t, ENNReal.toReal_nonneg, ENNReal.toReal_nonneg, ?_,
(average_union hd ht hsμ htμ hfs hft).symm⟩
calc
0 < μ.real s := ENNReal.toReal_pos hse hsμ
_ ≤ _ := le_add_of_nonneg_right ENNReal.toReal_nonneg
theorem average_mem_openSegment_compl_self [IsFiniteMeasure μ] {f : α → E} {s : Set α}
(hs : NullMeasurableSet s μ) (hs₀ : μ s ≠ 0) (hsc₀ : μ sᶜ ≠ 0) (hfi : Integrable f μ) :
⨍ x, f x ∂μ ∈ openSegment ℝ (⨍ x in s, f x ∂μ) (⨍ x in sᶜ, f x ∂μ) := by
simpa only [union_compl_self, restrict_univ] using
average_union_mem_openSegment aedisjoint_compl_right hs.compl hs₀ hsc₀ (measure_ne_top _ _)
(measure_ne_top _ _) hfi.integrableOn hfi.integrableOn
variable [CompleteSpace E]
@[simp]
theorem average_const (μ : Measure α) [IsFiniteMeasure μ] [h : NeZero μ] (c : E) :
⨍ _x, c ∂μ = c := by
rw [average, integral_const, measureReal_def, measure_univ, ENNReal.toReal_one, one_smul]
theorem setAverage_const {s : Set α} (hs₀ : μ s ≠ 0) (hs : μ s ≠ ∞) (c : E) :
⨍ _ in s, c ∂μ = c :=
have := NeZero.mk hs₀; have := Fact.mk hs.lt_top; average_const _ _
theorem integral_average (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) :
∫ _, ⨍ a, f a ∂μ ∂μ = ∫ x, f x ∂μ := by simp
theorem setIntegral_setAverage (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) (s : Set α) :
∫ _ in s, ⨍ a in s, f a ∂μ ∂μ = ∫ x in s, f x ∂μ :=
integral_average _ _
theorem integral_sub_average (μ : Measure α) [IsFiniteMeasure μ] (f : α → E) :
∫ x, f x - ⨍ a, f a ∂μ ∂μ = 0 := by
by_cases hf : Integrable f μ
· rw [integral_sub hf (integrable_const _), integral_average, sub_self]
refine integral_undef fun h => hf ?_
convert h.add (integrable_const (⨍ a, f a ∂μ))
exact (sub_add_cancel _ _).symm
theorem setAverage_sub_setAverage (hs : μ s ≠ ∞) (f : α → E) :
∫ x in s, f x - ⨍ a in s, f a ∂μ ∂μ = 0 :=
haveI : Fact (μ s < ∞) := ⟨lt_top_iff_ne_top.2 hs⟩
integral_sub_average _ _
theorem integral_average_sub [IsFiniteMeasure μ] (hf : Integrable f μ) :
∫ x, ⨍ a, f a ∂μ - f x ∂μ = 0 := by
rw [integral_sub (integrable_const _) hf, integral_average, sub_self]
theorem setIntegral_setAverage_sub (hs : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∫ x in s, ⨍ a in s, f a ∂μ - f x ∂μ = 0 :=
haveI : Fact (μ s < ∞) := ⟨lt_top_iff_ne_top.2 hs⟩
integral_average_sub hf
end NormedAddCommGroup
theorem ofReal_average {f : α → ℝ} (hf : Integrable f μ) (hf₀ : 0 ≤ᵐ[μ] f) :
ENNReal.ofReal (⨍ x, f x ∂μ) = (∫⁻ x, ENNReal.ofReal (f x) ∂μ) / μ univ := by
obtain rfl | hμ := eq_or_ne μ 0
· simp
· rw [average_eq, smul_eq_mul, measureReal_def, ← toReal_inv, ofReal_mul toReal_nonneg,
ofReal_toReal (inv_ne_top.2 <| measure_univ_ne_zero.2 hμ),
ofReal_integral_eq_lintegral_ofReal hf hf₀, ENNReal.div_eq_inv_mul]
theorem ofReal_setAverage {f : α → ℝ} (hf : IntegrableOn f s μ) (hf₀ : 0 ≤ᵐ[μ.restrict s] f) :
ENNReal.ofReal (⨍ x in s, f x ∂μ) = (∫⁻ x in s, ENNReal.ofReal (f x) ∂μ) / μ s := by
simpa using ofReal_average hf hf₀
theorem toReal_laverage {f : α → ℝ≥0∞} (hf : AEMeasurable f μ) (hf' : ∀ᵐ x ∂μ, f x ≠ ∞) :
(⨍⁻ x, f x ∂μ).toReal = ⨍ x, (f x).toReal ∂μ := by
rw [average_eq, laverage_eq, smul_eq_mul, toReal_div, div_eq_inv_mul, ←
integral_toReal hf (hf'.mono fun _ => lt_top_iff_ne_top.2), measureReal_def]
theorem toReal_setLAverage {f : α → ℝ≥0∞} (hf : AEMeasurable f (μ.restrict s))
(hf' : ∀ᵐ x ∂μ.restrict s, f x ≠ ∞) :
(⨍⁻ x in s, f x ∂μ).toReal = ⨍ x in s, (f x).toReal ∂μ := by
simpa [laverage_eq] using toReal_laverage hf hf'
@[deprecated (since := "2025-04-22")] alias toReal_setLaverage := toReal_setLAverage
/-! ### First moment method -/
section FirstMomentReal
variable {N : Set α} {f : α → ℝ}
/-- **First moment method**. An integrable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_setAverage_pos (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
0 < μ ({x ∈ s | f x ≤ ⨍ a in s, f a ∂μ}) := by
refine pos_iff_ne_zero.2 fun H => ?_
replace H : (μ.restrict s) {x | f x ≤ ⨍ a in s, f a ∂μ} = 0 := by
rwa [restrict_apply₀, inter_comm]
exact AEStronglyMeasurable.nullMeasurableSet_le hf.1 aestronglyMeasurable_const
haveI := Fact.mk hμ₁.lt_top
refine (integral_sub_average (μ.restrict s) f).not_gt ?_
refine (setIntegral_pos_iff_support_of_nonneg_ae ?_ ?_).2 ?_
· refine measure_mono_null (fun x hx ↦ ?_) H
simp only [Pi.zero_apply, sub_nonneg, mem_compl_iff, mem_setOf_eq, not_le] at hx
exact hx.le
· exact hf.sub (integrableOn_const.2 <| Or.inr <| lt_top_iff_ne_top.2 hμ₁)
· rwa [pos_iff_ne_zero, inter_comm, ← diff_compl, ← diff_inter_self_eq_diff, measure_diff_null]
refine measure_mono_null ?_ (measure_inter_eq_zero_of_restrict H)
exact inter_subset_inter_left _ fun a ha => (sub_eq_zero.1 <| of_not_not ha).le
/-- **First moment method**. An integrable function is greater than its mean on a set of positive
measure. -/
theorem measure_setAverage_le_pos (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
0 < μ ({x ∈ s | ⨍ a in s, f a ∂μ ≤ f x}) := by
simpa [integral_neg, neg_div] using measure_le_setAverage_pos hμ hμ₁ hf.neg
/-- **First moment method**. The minimum of an integrable function is smaller than its mean. -/
theorem exists_le_setAverage (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∃ x ∈ s, f x ≤ ⨍ a in s, f a ∂μ :=
let ⟨x, hx, h⟩ := nonempty_of_measure_ne_zero (measure_le_setAverage_pos hμ hμ₁ hf).ne'
⟨x, hx, h⟩
/-- **First moment method**. The maximum of an integrable function is greater than its mean. -/
theorem exists_setAverage_le (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : IntegrableOn f s μ) :
∃ x ∈ s, ⨍ a in s, f a ∂μ ≤ f x :=
let ⟨x, hx, h⟩ := nonempty_of_measure_ne_zero (measure_setAverage_le_pos hμ hμ₁ hf).ne'
⟨x, hx, h⟩
section FiniteMeasure
variable [IsFiniteMeasure μ]
/-- **First moment method**. An integrable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_average_pos (hμ : μ ≠ 0) (hf : Integrable f μ) :
0 < μ {x | f x ≤ ⨍ a, f a ∂μ} := by
simpa using measure_le_setAverage_pos (Measure.measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)
hf.integrableOn
/-- **First moment method**. An integrable function is greater than its mean on a set of positive
measure. -/
theorem measure_average_le_pos (hμ : μ ≠ 0) (hf : Integrable f μ) :
0 < μ {x | ⨍ a, f a ∂μ ≤ f x} := by
simpa using measure_setAverage_le_pos (Measure.measure_univ_ne_zero.2 hμ) (measure_ne_top _ _)
hf.integrableOn
/-- **First moment method**. The minimum of an integrable function is smaller than its mean. -/
theorem exists_le_average (hμ : μ ≠ 0) (hf : Integrable f μ) : ∃ x, f x ≤ ⨍ a, f a ∂μ :=
let ⟨x, hx⟩ := nonempty_of_measure_ne_zero (measure_le_average_pos hμ hf).ne'
⟨x, hx⟩
/-- **First moment method**. The maximum of an integrable function is greater than its mean. -/
theorem exists_average_le (hμ : μ ≠ 0) (hf : Integrable f μ) : ∃ x, ⨍ a, f a ∂μ ≤ f x :=
let ⟨x, hx⟩ := nonempty_of_measure_ne_zero (measure_average_le_pos hμ hf).ne'
⟨x, hx⟩
/-- **First moment method**. The minimum of an integrable function is smaller than its mean, while
avoiding a null set. -/
theorem exists_not_mem_null_le_average (hμ : μ ≠ 0) (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ f x ≤ ⨍ a, f a ∂μ := by
have := measure_le_average_pos hμ hf
rw [← measure_diff_null hN] at this
obtain ⟨x, hx, hxN⟩ := nonempty_of_measure_ne_zero this.ne'
exact ⟨x, hxN, hx⟩
/-- **First moment method**. The maximum of an integrable function is greater than its mean, while
avoiding a null set. -/
theorem exists_not_mem_null_average_le (hμ : μ ≠ 0) (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ ⨍ a, f a ∂μ ≤ f x := by
simpa [integral_neg, neg_div] using exists_not_mem_null_le_average hμ hf.neg hN
end FiniteMeasure
section ProbabilityMeasure
variable [IsProbabilityMeasure μ]
/-- **First moment method**. An integrable function is smaller than its integral on a set of
positive measure. -/
theorem measure_le_integral_pos (hf : Integrable f μ) : 0 < μ {x | f x ≤ ∫ a, f a ∂μ} := by
simpa only [average_eq_integral] using
measure_le_average_pos (IsProbabilityMeasure.ne_zero μ) hf
/-- **First moment method**. An integrable function is greater than its integral on a set of
positive measure. -/
theorem measure_integral_le_pos (hf : Integrable f μ) : 0 < μ {x | ∫ a, f a ∂μ ≤ f x} := by
simpa only [average_eq_integral] using
measure_average_le_pos (IsProbabilityMeasure.ne_zero μ) hf
/-- **First moment method**. The minimum of an integrable function is smaller than its integral. -/
theorem exists_le_integral (hf : Integrable f μ) : ∃ x, f x ≤ ∫ a, f a ∂μ := by
simpa only [average_eq_integral] using exists_le_average (IsProbabilityMeasure.ne_zero μ) hf
/-- **First moment method**. The maximum of an integrable function is greater than its integral. -/
theorem exists_integral_le (hf : Integrable f μ) : ∃ x, ∫ a, f a ∂μ ≤ f x := by
simpa only [average_eq_integral] using exists_average_le (IsProbabilityMeasure.ne_zero μ) hf
/-- **First moment method**. The minimum of an integrable function is smaller than its integral,
while avoiding a null set. -/
theorem exists_not_mem_null_le_integral (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ f x ≤ ∫ a, f a ∂μ := by
simpa only [average_eq_integral] using
exists_not_mem_null_le_average (IsProbabilityMeasure.ne_zero μ) hf hN
/-- **First moment method**. The maximum of an integrable function is greater than its integral,
while avoiding a null set. -/
theorem exists_not_mem_null_integral_le (hf : Integrable f μ) (hN : μ N = 0) :
∃ x, x ∉ N ∧ ∫ a, f a ∂μ ≤ f x := by
simpa only [average_eq_integral] using
exists_not_mem_null_average_le (IsProbabilityMeasure.ne_zero μ) hf hN
end ProbabilityMeasure
end FirstMomentReal
section FirstMomentENNReal
variable {N : Set α} {f : α → ℝ≥0∞}
/-- **First moment method**. A measurable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_setLAverage_pos (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞)
(hf : AEMeasurable f (μ.restrict s)) : 0 < μ {x ∈ s | f x ≤ ⨍⁻ a in s, f a ∂μ} := by
obtain h | h := eq_or_ne (∫⁻ a in s, f a ∂μ) ∞
· simpa [mul_top, hμ₁, laverage, h, top_div_of_ne_top hμ₁, pos_iff_ne_zero] using hμ
have := measure_le_setAverage_pos hμ hμ₁ (integrable_toReal_of_lintegral_ne_top hf h)
rw [← setOf_inter_eq_sep, ← Measure.restrict_apply₀
(hf.aestronglyMeasurable.nullMeasurableSet_le aestronglyMeasurable_const)]
rw [← setOf_inter_eq_sep, ← Measure.restrict_apply₀
(hf.ennreal_toReal.aestronglyMeasurable.nullMeasurableSet_le aestronglyMeasurable_const),
← measure_diff_null (measure_eq_top_of_lintegral_ne_top hf h)] at this
refine this.trans_le (measure_mono ?_)
rintro x ⟨hfx, hx⟩
dsimp at hfx
rwa [← toReal_laverage hf, toReal_le_toReal hx (setLAverage_lt_top h).ne] at hfx
simp_rw [ae_iff, not_ne_iff]
exact measure_eq_top_of_lintegral_ne_top hf h
@[deprecated (since := "2025-04-22")] alias measure_le_setLaverage_pos := measure_le_setLAverage_pos
/-- **First moment method**. A measurable function is greater than its mean on a set of positive
measure. -/
theorem measure_setLAverage_le_pos (hμ : μ s ≠ 0) (hs : NullMeasurableSet s μ)
(hint : ∫⁻ a in s, f a ∂μ ≠ ∞) : 0 < μ {x ∈ s | ⨍⁻ a in s, f a ∂μ ≤ f x} := by
obtain hμ₁ | hμ₁ := eq_or_ne (μ s) ∞
· simp [setLAverage_eq, hμ₁]
obtain ⟨g, hg, hgf, hfg⟩ := exists_measurable_le_lintegral_eq (μ.restrict s) f
have hfg' : ⨍⁻ a in s, f a ∂μ = ⨍⁻ a in s, g a ∂μ := by simp_rw [laverage_eq, hfg]
rw [hfg] at hint
have :=
measure_setAverage_le_pos hμ hμ₁ (integrable_toReal_of_lintegral_ne_top hg.aemeasurable hint)
simp_rw [← setOf_inter_eq_sep, ← Measure.restrict_apply₀' hs, hfg']
rw [← setOf_inter_eq_sep, ← Measure.restrict_apply₀' hs, ←
measure_diff_null (measure_eq_top_of_lintegral_ne_top hg.aemeasurable hint)] at this
refine this.trans_le (measure_mono ?_)
rintro x ⟨hfx, hx⟩
dsimp at hfx
rw [← toReal_laverage hg.aemeasurable, toReal_le_toReal (setLAverage_lt_top hint).ne hx] at hfx
· exact hfx.trans (hgf _)
· simp_rw [ae_iff, not_ne_iff]
exact measure_eq_top_of_lintegral_ne_top hg.aemeasurable hint
@[deprecated (since := "2025-04-22")] alias measure_setLaverage_le_pos := measure_setLAverage_le_pos
/-- **First moment method**. The minimum of a measurable function is smaller than its mean. -/
theorem exists_le_setLAverage (hμ : μ s ≠ 0) (hμ₁ : μ s ≠ ∞) (hf : AEMeasurable f (μ.restrict s)) :
∃ x ∈ s, f x ≤ ⨍⁻ a in s, f a ∂μ :=
let ⟨x, hx, h⟩ := nonempty_of_measure_ne_zero (measure_le_setLAverage_pos hμ hμ₁ hf).ne'
⟨x, hx, h⟩
@[deprecated (since := "2025-04-22")] alias exists_le_setLaverage := exists_le_setLAverage
/-- **First moment method**. The maximum of a measurable function is greater than its mean. -/
theorem exists_setLAverage_le (hμ : μ s ≠ 0) (hs : NullMeasurableSet s μ)
(hint : ∫⁻ a in s, f a ∂μ ≠ ∞) : ∃ x ∈ s, ⨍⁻ a in s, f a ∂μ ≤ f x :=
let ⟨x, hx, h⟩ := nonempty_of_measure_ne_zero (measure_setLAverage_le_pos hμ hs hint).ne'
⟨x, hx, h⟩
@[deprecated (since := "2025-04-22")] alias exists_setLaverage_le := exists_setLAverage_le
/-- **First moment method**. A measurable function is greater than its mean on a set of positive
measure. -/
theorem measure_laverage_le_pos (hμ : μ ≠ 0) (hint : ∫⁻ a, f a ∂μ ≠ ∞) :
0 < μ {x | ⨍⁻ a, f a ∂μ ≤ f x} := by
simpa [hint] using
@measure_setLAverage_le_pos _ _ _ _ f (measure_univ_ne_zero.2 hμ) nullMeasurableSet_univ
/-- **First moment method**. The maximum of a measurable function is greater than its mean. -/
theorem exists_laverage_le (hμ : μ ≠ 0) (hint : ∫⁻ a, f a ∂μ ≠ ∞) : ∃ x, ⨍⁻ a, f a ∂μ ≤ f x :=
let ⟨x, hx⟩ := nonempty_of_measure_ne_zero (measure_laverage_le_pos hμ hint).ne'
⟨x, hx⟩
/-- **First moment method**. The maximum of a measurable function is greater than its mean, while
avoiding a null set. -/
| Mathlib/MeasureTheory/Integral/Average.lean | 682 | 700 | theorem exists_not_mem_null_laverage_le (hμ : μ ≠ 0) (hint : ∫⁻ a : α, f a ∂μ ≠ ∞) (hN : μ N = 0) :
∃ x, x ∉ N ∧ ⨍⁻ a, f a ∂μ ≤ f x := by | have := measure_laverage_le_pos hμ hint
rw [← measure_diff_null hN] at this
obtain ⟨x, hx, hxN⟩ := nonempty_of_measure_ne_zero this.ne'
exact ⟨x, hxN, hx⟩
section FiniteMeasure
variable [IsFiniteMeasure μ]
/-- **First moment method**. A measurable function is smaller than its mean on a set of positive
measure. -/
theorem measure_le_laverage_pos (hμ : μ ≠ 0) (hf : AEMeasurable f μ) :
0 < μ {x | f x ≤ ⨍⁻ a, f a ∂μ} := by
simpa using
measure_le_setLAverage_pos (measure_univ_ne_zero.2 hμ) (measure_ne_top _ _) hf.restrict
/-- **First moment method**. The minimum of a measurable function is smaller than its mean. -/
theorem exists_le_laverage (hμ : μ ≠ 0) (hf : AEMeasurable f μ) : ∃ x, f x ≤ ⨍⁻ a, f a ∂μ := |
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Robert Y. Lewis
-/
import Mathlib.Algebra.MvPolynomial.Counit
import Mathlib.Algebra.MvPolynomial.Invertible
import Mathlib.RingTheory.WittVector.Defs
/-!
# Witt vectors
This file verifies that the ring operations on `WittVector p R`
satisfy the axioms of a commutative ring.
## Main definitions
* `WittVector.map`: lifts a ring homomorphism `R →+* S` to a ring homomorphism `𝕎 R →+* 𝕎 S`.
* `WittVector.ghostComponent n x`: evaluates the `n`th Witt polynomial
on the first `n` coefficients of `x`, producing a value in `R`.
This is a ring homomorphism.
* `WittVector.ghostMap`: a ring homomorphism `𝕎 R →+* (ℕ → R)`, obtained by packaging
all the ghost components together.
If `p` is invertible in `R`, then the ghost map is an equivalence,
which we use to define the ring operations on `𝕎 R`.
* `WittVector.CommRing`: the ring structure induced by the ghost components.
## Notation
We use notation `𝕎 R`, entered `\bbW`, for the Witt vectors over `R`.
## Implementation details
As we prove that the ghost components respect the ring operations, we face a number of repetitive
proofs. To avoid duplicating code we factor these proofs into a custom tactic, only slightly more
powerful than a tactic macro. This tactic is not particularly useful outside of its applications
in this file.
## References
* [Hazewinkel, *Witt Vectors*][Haze09]
* [Commelin and Lewis, *Formalizing the Ring of Witt Vectors*][CL21]
-/
noncomputable section
open MvPolynomial Function
variable {p : ℕ} {R S : Type*} [CommRing R] [CommRing S]
variable {α : Type*} {β : Type*}
local notation "𝕎" => WittVector p
local notation "W_" => wittPolynomial p
-- type as `\bbW`
open scoped Witt
namespace WittVector
/-- `f : α → β` induces a map from `𝕎 α` to `𝕎 β` by applying `f` componentwise.
If `f` is a ring homomorphism, then so is `f`, see `WittVector.map f`. -/
def mapFun (f : α → β) : 𝕎 α → 𝕎 β := fun x => mk _ (f ∘ x.coeff)
namespace mapFun
-- Porting note: switched the proof to tactic mode. I think that `ext` was the issue.
theorem injective (f : α → β) (hf : Injective f) : Injective (mapFun f : 𝕎 α → 𝕎 β) := by
intros _ _ h
ext p
exact hf (congr_arg (fun x => coeff x p) h :)
theorem surjective (f : α → β) (hf : Surjective f) : Surjective (mapFun f : 𝕎 α → 𝕎 β) := fun x =>
⟨mk _ fun n => Classical.choose <| hf <| x.coeff n,
by ext n; simp only [mapFun, coeff_mk, comp_apply, Classical.choose_spec (hf (x.coeff n))]⟩
/-- Auxiliary tactic for showing that `mapFun` respects the ring operations. -/
-- porting note: a very crude port.
macro "map_fun_tac" : tactic => `(tactic| (
ext n
simp only [mapFun, mk, comp_apply, zero_coeff, map_zero,
-- Porting note: the lemmas on the next line do not have the `simp` tag in mathlib4
add_coeff, sub_coeff, mul_coeff, neg_coeff, nsmul_coeff, zsmul_coeff, pow_coeff,
peval, map_aeval, algebraMap_int_eq, coe_eval₂Hom] <;>
try { cases n <;> simp <;> done } <;> -- Porting note: this line solves `one`
apply eval₂Hom_congr (RingHom.ext_int _ _) _ rfl <;>
ext ⟨i, k⟩ <;>
fin_cases i <;> rfl))
variable [Fact p.Prime]
-- Porting note: using `(x y : 𝕎 R)` instead of `(x y : WittVector p R)` produced sorries.
variable (f : R →+* S) (x y : WittVector p R)
-- and until `pow`.
-- We do not tag these lemmas as `@[simp]` because they will be bundled in `map` later on.
theorem zero : mapFun f (0 : 𝕎 R) = 0 := by map_fun_tac
theorem one : mapFun f (1 : 𝕎 R) = 1 := by map_fun_tac
theorem add : mapFun f (x + y) = mapFun f x + mapFun f y := by map_fun_tac
theorem sub : mapFun f (x - y) = mapFun f x - mapFun f y := by map_fun_tac
theorem mul : mapFun f (x * y) = mapFun f x * mapFun f y := by map_fun_tac
theorem neg : mapFun f (-x) = -mapFun f x := by map_fun_tac
theorem nsmul (n : ℕ) (x : WittVector p R) : mapFun f (n • x) = n • mapFun f x := by map_fun_tac
theorem zsmul (z : ℤ) (x : WittVector p R) : mapFun f (z • x) = z • mapFun f x := by map_fun_tac
| Mathlib/RingTheory/WittVector/Basic.lean | 114 | 114 | theorem pow (n : ℕ) : mapFun f (x ^ n) = mapFun f x ^ n := by | map_fun_tac |
/-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.Basic
import Mathlib.RingTheory.Artinian.Module
/-!
# Lie subalgebras
This file defines Lie subalgebras of a Lie algebra and provides basic related definitions and
results.
## Main definitions
* `LieSubalgebra`
* `LieSubalgebra.incl`
* `LieSubalgebra.map`
* `LieHom.range`
* `LieEquiv.ofInjective`
* `LieEquiv.ofEq`
* `LieEquiv.ofSubalgebras`
## Tags
lie algebra, lie subalgebra
-/
universe u v w w₁ w₂
section LieSubalgebra
variable (R : Type u) (L : Type v) [CommRing R] [LieRing L] [LieAlgebra R L]
/-- A Lie subalgebra of a Lie algebra is submodule that is closed under the Lie bracket.
This is a sufficient condition for the subset itself to form a Lie algebra. -/
structure LieSubalgebra extends Submodule R L where
/-- A Lie subalgebra is closed under Lie bracket. -/
lie_mem' : ∀ {x y}, x ∈ carrier → y ∈ carrier → ⁅x, y⁆ ∈ carrier
/-- The zero algebra is a subalgebra of any Lie algebra. -/
instance : Zero (LieSubalgebra R L) :=
⟨⟨0, @fun x y hx _hy ↦ by
rw [(Submodule.mem_bot R).1 hx, zero_lie]
exact Submodule.zero_mem 0⟩⟩
instance : Inhabited (LieSubalgebra R L) :=
⟨0⟩
instance : Coe (LieSubalgebra R L) (Submodule R L) :=
⟨LieSubalgebra.toSubmodule⟩
namespace LieSubalgebra
instance : SetLike (LieSubalgebra R L) L where
coe L' := L'.carrier
coe_injective' L' L'' h := by
rcases L' with ⟨⟨⟩⟩
rcases L'' with ⟨⟨⟩⟩
congr
exact SetLike.coe_injective' h
instance : AddSubgroupClass (LieSubalgebra R L) L where
add_mem := Submodule.add_mem _
zero_mem L' := L'.zero_mem'
neg_mem {L'} x hx := show -x ∈ (L' : Submodule R L) from neg_mem hx
/-- A Lie subalgebra forms a new Lie ring. -/
instance lieRing (L' : LieSubalgebra R L) : LieRing L' where
bracket x y := ⟨⁅x.val, y.val⁆, L'.lie_mem' x.property y.property⟩
lie_add := by
intros
apply SetCoe.ext
apply lie_add
add_lie := by
intros
apply SetCoe.ext
apply add_lie
lie_self := by
intros
apply SetCoe.ext
apply lie_self
leibniz_lie := by
intros
apply SetCoe.ext
apply leibniz_lie
section
variable {R₁ : Type*} [Semiring R₁]
/-- A Lie subalgebra inherits module structures from `L`. -/
instance [SMul R₁ R] [Module R₁ L] [IsScalarTower R₁ R L] (L' : LieSubalgebra R L) : Module R₁ L' :=
L'.toSubmodule.module'
instance [SMul R₁ R] [SMul R₁ᵐᵒᵖ R] [Module R₁ L] [Module R₁ᵐᵒᵖ L] [IsScalarTower R₁ R L]
[IsScalarTower R₁ᵐᵒᵖ R L] [IsCentralScalar R₁ L] (L' : LieSubalgebra R L) :
IsCentralScalar R₁ L' :=
L'.toSubmodule.isCentralScalar
instance [SMul R₁ R] [Module R₁ L] [IsScalarTower R₁ R L] (L' : LieSubalgebra R L) :
IsScalarTower R₁ R L' :=
L'.toSubmodule.isScalarTower
instance (L' : LieSubalgebra R L) [IsNoetherian R L] : IsNoetherian R L' :=
isNoetherian_submodule' _
instance (L' : LieSubalgebra R L) [IsArtinian R L] : IsArtinian R L' :=
isArtinian_submodule' _
end
/-- A Lie subalgebra forms a new Lie algebra. -/
instance lieAlgebra (L' : LieSubalgebra R L) : LieAlgebra R L' where
lie_smul := by
{ intros
apply SetCoe.ext
apply lie_smul }
variable {R L}
variable (L' : LieSubalgebra R L)
@[simp]
protected theorem zero_mem : (0 : L) ∈ L' :=
zero_mem L'
protected theorem add_mem {x y : L} : x ∈ L' → y ∈ L' → (x + y : L) ∈ L' :=
add_mem
protected theorem sub_mem {x y : L} : x ∈ L' → y ∈ L' → (x - y : L) ∈ L' :=
sub_mem
theorem smul_mem (t : R) {x : L} (h : x ∈ L') : t • x ∈ L' :=
(L' : Submodule R L).smul_mem t h
theorem lie_mem {x y : L} (hx : x ∈ L') (hy : y ∈ L') : (⁅x, y⁆ : L) ∈ L' :=
L'.lie_mem' hx hy
theorem mem_carrier {x : L} : x ∈ L'.carrier ↔ x ∈ (L' : Set L) :=
Iff.rfl
@[simp]
theorem mem_mk_iff (S : Set L) (h₁ h₂ h₃ h₄) {x : L} :
x ∈ (⟨⟨⟨⟨S, h₁⟩, h₂⟩, h₃⟩, h₄⟩ : LieSubalgebra R L) ↔ x ∈ S :=
Iff.rfl
@[simp]
theorem mem_toSubmodule {x : L} : x ∈ (L' : Submodule R L) ↔ x ∈ L' :=
Iff.rfl
@[deprecated (since := "2024-12-30")] alias mem_coe_submodule := mem_toSubmodule
theorem mem_coe {x : L} : x ∈ (L' : Set L) ↔ x ∈ L' :=
Iff.rfl
@[simp, norm_cast]
theorem coe_bracket (x y : L') : (↑⁅x, y⁆ : L) = ⁅(↑x : L), ↑y⁆ :=
rfl
theorem ext_iff (x y : L') : x = y ↔ (x : L) = y :=
Subtype.ext_iff
theorem coe_zero_iff_zero (x : L') : (x : L) = 0 ↔ x = 0 :=
(ext_iff L' x 0).symm
@[ext]
theorem ext (L₁' L₂' : LieSubalgebra R L) (h : ∀ x, x ∈ L₁' ↔ x ∈ L₂') : L₁' = L₂' :=
SetLike.ext h
theorem ext_iff' (L₁' L₂' : LieSubalgebra R L) : L₁' = L₂' ↔ ∀ x, x ∈ L₁' ↔ x ∈ L₂' :=
SetLike.ext_iff
@[simp]
theorem mk_coe (S : Set L) (h₁ h₂ h₃ h₄) :
((⟨⟨⟨⟨S, h₁⟩, h₂⟩, h₃⟩, h₄⟩ : LieSubalgebra R L) : Set L) = S :=
rfl
theorem toSubmodule_mk (p : Submodule R L) (h) :
(({ p with lie_mem' := h } : LieSubalgebra R L) : Submodule R L) = p := by
cases p
rfl
@[deprecated (since := "2024-12-30")] alias coe_to_submodule_mk := toSubmodule_mk
theorem coe_injective : Function.Injective ((↑) : LieSubalgebra R L → Set L) :=
SetLike.coe_injective
@[norm_cast]
theorem coe_set_eq (L₁' L₂' : LieSubalgebra R L) : (L₁' : Set L) = L₂' ↔ L₁' = L₂' :=
SetLike.coe_set_eq
theorem toSubmodule_injective : Function.Injective ((↑) : LieSubalgebra R L → Submodule R L) :=
fun L₁' L₂' h ↦ by
rw [SetLike.ext'_iff] at h
rw [← coe_set_eq]
exact h
@[deprecated (since := "2024-12-30")] alias to_submodule_injective := toSubmodule_injective
@[simp]
theorem toSubmodule_inj (L₁' L₂' : LieSubalgebra R L) :
(L₁' : Submodule R L) = (L₂' : Submodule R L) ↔ L₁' = L₂' :=
toSubmodule_injective.eq_iff
@[deprecated (since := "2024-12-30")] alias coe_to_submodule_inj := toSubmodule_inj
@[deprecated (since := "2024-12-29")] alias toSubmodule_eq_iff := toSubmodule_inj
theorem coe_toSubmodule : ((L' : Submodule R L) : Set L) = L' :=
rfl
@[deprecated (since := "2024-12-30")] alias coe_to_submodule := coe_toSubmodule
section LieModule
variable {M : Type w} [AddCommGroup M] [LieRingModule L M]
variable {N : Type w₁} [AddCommGroup N] [LieRingModule L N] [Module R N]
instance : Bracket L' M where
bracket x m := ⁅(x : L), m⁆
@[simp]
theorem coe_bracket_of_module (x : L') (m : M) : ⁅x, m⁆ = ⁅(x : L), m⁆ :=
rfl
instance : IsLieTower L' L M where
leibniz_lie x y m := leibniz_lie x.val y m
/-- Given a Lie algebra `L` containing a Lie subalgebra `L' ⊆ L`, together with a Lie ring module
`M` of `L`, we may regard `M` as a Lie ring module of `L'` by restriction. -/
instance lieRingModule : LieRingModule L' M where
add_lie x y m := add_lie (x : L) y m
lie_add x y m := lie_add (x : L) y m
leibniz_lie x y m := leibniz_lie x (y : L) m
variable [Module R M]
/-- Given a Lie algebra `L` containing a Lie subalgebra `L' ⊆ L`, together with a Lie module `M` of
`L`, we may regard `M` as a Lie module of `L'` by restriction. -/
instance lieModule [LieModule R L M] : LieModule R L' M where
smul_lie t x m := by
rw [coe_bracket_of_module, Submodule.coe_smul_of_tower, smul_lie, coe_bracket_of_module]
lie_smul t x m := by simp only [coe_bracket_of_module, lie_smul]
/-- An `L`-equivariant map of Lie modules `M → N` is `L'`-equivariant for any Lie subalgebra
`L' ⊆ L`. -/
def _root_.LieModuleHom.restrictLie (f : M →ₗ⁅R,L⁆ N) (L' : LieSubalgebra R L) : M →ₗ⁅R,L'⁆ N :=
{ (f : M →ₗ[R] N) with map_lie' := @fun x m ↦ f.map_lie (↑x) m }
@[simp]
theorem _root_.LieModuleHom.coe_restrictLie (f : M →ₗ⁅R,L⁆ N) : ⇑(f.restrictLie L') = f :=
rfl
end LieModule
/-- The embedding of a Lie subalgebra into the ambient space as a morphism of Lie algebras. -/
def incl : L' →ₗ⁅R⁆ L :=
{ (L' : Submodule R L).subtype with
map_lie' := rfl }
@[simp]
theorem coe_incl : ⇑L'.incl = ((↑) : L' → L) :=
rfl
/-- The embedding of a Lie subalgebra into the ambient space as a morphism of Lie modules. -/
def incl' : L' →ₗ⁅R,L'⁆ L :=
{ (L' : Submodule R L).subtype with
map_lie' := rfl }
@[simp]
theorem coe_incl' : ⇑L'.incl' = ((↑) : L' → L) :=
rfl
end LieSubalgebra
variable {R L}
variable {L₂ : Type w} [LieRing L₂] [LieAlgebra R L₂]
variable (f : L →ₗ⁅R⁆ L₂)
namespace LieHom
/-- The range of a morphism of Lie algebras is a Lie subalgebra. -/
def range : LieSubalgebra R L₂ :=
{ LinearMap.range (f : L →ₗ[R] L₂) with
lie_mem' := by
rintro - - ⟨x, rfl⟩ ⟨y, rfl⟩
exact ⟨⁅x, y⁆, f.map_lie x y⟩ }
@[simp]
theorem range_coe : (f.range : Set L₂) = Set.range f :=
LinearMap.range_coe (f : L →ₗ[R] L₂)
@[simp]
theorem mem_range (x : L₂) : x ∈ f.range ↔ ∃ y : L, f y = x :=
LinearMap.mem_range
theorem mem_range_self (x : L) : f x ∈ f.range :=
LinearMap.mem_range_self (f : L →ₗ[R] L₂) x
/-- We can restrict a morphism to a (surjective) map to its range. -/
def rangeRestrict : L →ₗ⁅R⁆ f.range :=
{ (f : L →ₗ[R] L₂).rangeRestrict with
map_lie' := @fun x y ↦ by
apply Subtype.ext
exact f.map_lie x y }
@[simp]
theorem rangeRestrict_apply (x : L) : f.rangeRestrict x = ⟨f x, f.mem_range_self x⟩ :=
rfl
theorem surjective_rangeRestrict : Function.Surjective f.rangeRestrict := by
rintro ⟨y, hy⟩
rw [mem_range] at hy; obtain ⟨x, rfl⟩ := hy
use x
simp only [Subtype.mk_eq_mk, rangeRestrict_apply]
/-- A Lie algebra is equivalent to its range under an injective Lie algebra morphism. -/
noncomputable def equivRangeOfInjective (h : Function.Injective f) : L ≃ₗ⁅R⁆ f.range :=
LieEquiv.ofBijective f.rangeRestrict
⟨fun x y hxy ↦ by
simp only [Subtype.mk_eq_mk, rangeRestrict_apply] at hxy
exact h hxy, f.surjective_rangeRestrict⟩
@[simp]
theorem equivRangeOfInjective_apply (h : Function.Injective f) (x : L) :
f.equivRangeOfInjective h x = ⟨f x, mem_range_self f x⟩ :=
rfl
end LieHom
theorem Submodule.exists_lieSubalgebra_coe_eq_iff (p : Submodule R L) :
(∃ K : LieSubalgebra R L, ↑K = p) ↔ ∀ x y : L, x ∈ p → y ∈ p → ⁅x, y⁆ ∈ p := by
constructor
· rintro ⟨K, rfl⟩ _ _
exact K.lie_mem'
· intro h
use { p with lie_mem' := h _ _ }
namespace LieSubalgebra
variable (K K' : LieSubalgebra R L) (K₂ : LieSubalgebra R L₂)
@[simp]
theorem incl_range : K.incl.range = K := by
rw [← toSubmodule_inj]
exact (K : Submodule R L).range_subtype
/-- The image of a Lie subalgebra under a Lie algebra morphism is a Lie subalgebra of the
codomain. -/
def map : LieSubalgebra R L₂ :=
{ (K : Submodule R L).map (f : L →ₗ[R] L₂) with
lie_mem' {x y} hx hy := by
simp only [AddSubsemigroup.mem_carrier] at hx hy
rcases hx with ⟨x', hx', rfl⟩
rcases hy with ⟨y', hy', rfl⟩
simpa using ⟨⁅x', y'⁆, K.lie_mem hx' hy', f.map_lie x' y'⟩ }
@[simp]
theorem mem_map (x : L₂) : x ∈ K.map f ↔ ∃ y : L, y ∈ K ∧ f y = x :=
Submodule.mem_map
-- TODO Rename and state for homs instead of equivs.
theorem mem_map_submodule (e : L ≃ₗ⁅R⁆ L₂) (x : L₂) :
x ∈ K.map (e : L →ₗ⁅R⁆ L₂) ↔ x ∈ (K : Submodule R L).map (e : L →ₗ[R] L₂) :=
Iff.rfl
/-- The preimage of a Lie subalgebra under a Lie algebra morphism is a Lie subalgebra of the
domain. -/
def comap : LieSubalgebra R L :=
{ (K₂ : Submodule R L₂).comap (f : L →ₗ[R] L₂) with
lie_mem' := @fun x y hx hy ↦ by
suffices ⁅f x, f y⁆ ∈ K₂ by simp [this]
exact K₂.lie_mem hx hy }
section LatticeStructure
open Set
instance : PartialOrder (LieSubalgebra R L) :=
{ PartialOrder.lift ((↑) : LieSubalgebra R L → Set L) coe_injective with
le := fun N N' ↦ ∀ ⦃x⦄, x ∈ N → x ∈ N' }
theorem le_def : K ≤ K' ↔ (K : Set L) ⊆ K' :=
Iff.rfl
@[simp]
theorem toSubmodule_le_toSubmodule : (K : Submodule R L) ≤ K' ↔ K ≤ K' :=
Iff.rfl
@[deprecated (since := "2024-12-30")]
alias coe_submodule_le_coe_submodule := toSubmodule_le_toSubmodule
instance : Bot (LieSubalgebra R L) :=
⟨0⟩
@[simp]
theorem bot_coe : ((⊥ : LieSubalgebra R L) : Set L) = {0} :=
rfl
@[simp]
theorem bot_toSubmodule : ((⊥ : LieSubalgebra R L) : Submodule R L) = ⊥ :=
rfl
@[deprecated (since := "2024-12-30")] alias bot_coe_submodule := bot_toSubmodule
@[simp]
theorem mem_bot (x : L) : x ∈ (⊥ : LieSubalgebra R L) ↔ x = 0 :=
mem_singleton_iff
instance : Top (LieSubalgebra R L) :=
⟨{ (⊤ : Submodule R L) with lie_mem' := @fun x y _ _ ↦ mem_univ ⁅x, y⁆ }⟩
@[simp]
theorem top_coe : ((⊤ : LieSubalgebra R L) : Set L) = univ :=
rfl
@[simp]
theorem top_toSubmodule : ((⊤ : LieSubalgebra R L) : Submodule R L) = ⊤ :=
rfl
@[deprecated (since := "2024-12-30")] alias top_coe_submodule := top_toSubmodule
@[simp]
theorem mem_top (x : L) : x ∈ (⊤ : LieSubalgebra R L) :=
mem_univ x
theorem _root_.LieHom.range_eq_map : f.range = map f ⊤ := by
ext
simp
instance : Min (LieSubalgebra R L) :=
⟨fun K K' ↦
{ (K ⊓ K' : Submodule R L) with
lie_mem' := fun hx hy ↦ mem_inter (K.lie_mem hx.1 hy.1) (K'.lie_mem hx.2 hy.2) }⟩
instance : InfSet (LieSubalgebra R L) :=
⟨fun S ↦
{ sInf {(s : Submodule R L) | s ∈ S} with
lie_mem' := @fun x y hx hy ↦ by
simp only [Submodule.mem_carrier, mem_iInter, Submodule.sInf_coe, mem_setOf_eq,
forall_apply_eq_imp_iff₂, exists_imp, and_imp] at hx hy ⊢
intro K hK
exact K.lie_mem (hx K hK) (hy K hK) }⟩
@[simp]
theorem inf_coe : (↑(K ⊓ K') : Set L) = (K : Set L) ∩ (K' : Set L) :=
rfl
@[simp]
theorem sInf_toSubmodule (S : Set (LieSubalgebra R L)) :
(↑(sInf S) : Submodule R L) = sInf {(s : Submodule R L) | s ∈ S} :=
rfl
@[deprecated (since := "2024-12-30")] alias sInf_coe_to_submodule := sInf_toSubmodule
@[simp]
| Mathlib/Algebra/Lie/Subalgebra.lean | 459 | 461 | theorem sInf_coe (S : Set (LieSubalgebra R L)) : (↑(sInf S) : Set L) = ⋂ s ∈ S, (s : Set L) := by | rw [← coe_toSubmodule, sInf_toSubmodule, Submodule.sInf_coe]
ext x |
/-
Copyright (c) 2023 Scott Carnahan. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Carnahan
-/
import Mathlib.Algebra.Group.NatPowAssoc
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Eval.SMul
/-!
# Scalar-multiple polynomial evaluation
This file defines polynomial evaluation via scalar multiplication. Our polynomials have
coefficients in a semiring `R`, and we evaluate at a weak form of `R`-algebra, namely an additive
commutative monoid with an action of `R` and a notion of natural number power. This
is a generalization of `Algebra.Polynomial.Eval`.
## Main definitions
* `Polynomial.smeval`: function for evaluating a polynomial with coefficients in a `Semiring`
`R` at an element `x` of an `AddCommMonoid` `S` that has natural number powers and an `R`-action.
* `smeval.linearMap`: the `smeval` function as an `R`-linear map, when `S` is an `R`-module.
* `smeval.algebraMap`: the `smeval` function as an `R`-algebra map, when `S` is an `R`-algebra.
## Main results
* `smeval_monomial`: monomials evaluate as we expect.
* `smeval_add`, `smeval_smul`: linearity of evaluation, given an `R`-module.
* `smeval_mul`, `smeval_comp`: multiplicativity of evaluation, given power-associativity.
* `eval₂_smulOneHom_eq_smeval`, `leval_eq_smeval.linearMap`,
`aeval_eq_smeval`, etc.: comparisons
## TODO
* `smeval_neg` and `smeval_intCast` for `R` a ring and `S` an `AddCommGroup`.
* Nonunital evaluation for polynomials with vanishing constant term for `Pow S ℕ+` (different file?)
-/
namespace Polynomial
section MulActionWithZero
variable {R : Type*} [Semiring R] (r : R) (p : R[X]) {S : Type*} [AddCommMonoid S] [Pow S ℕ]
[MulActionWithZero R S] (x : S)
/-- Scalar multiplication together with taking a natural number power. -/
def smul_pow : ℕ → R → S := fun n r => r • x^n
/-- Evaluate a polynomial `p` in the scalar semiring `R` at an element `x` in the target `S` using
scalar multiple `R`-action. -/
irreducible_def smeval : S := p.sum (smul_pow x)
theorem smeval_eq_sum : p.smeval x = p.sum (smul_pow x) := by rw [smeval_def]
@[simp]
theorem smeval_C : (C r).smeval x = r • x ^ 0 := by
simp only [smeval_eq_sum, smul_pow, zero_smul, sum_C_index]
@[simp]
theorem smeval_monomial (n : ℕ) :
(monomial n r).smeval x = r • x ^ n := by
simp only [smeval_eq_sum, smul_pow, zero_smul, sum_monomial_index]
theorem eval_eq_smeval : p.eval r = p.smeval r := by
rw [eval_eq_sum, smeval_eq_sum]
rfl
theorem eval₂_smulOneHom_eq_smeval (R : Type*) [Semiring R] {S : Type*} [Semiring S] [Module R S]
[IsScalarTower R S S] (p : R[X]) (x : S) :
p.eval₂ RingHom.smulOneHom x = p.smeval x := by
rw [smeval_eq_sum, eval₂_eq_sum]
congr 1 with e a
simp only [RingHom.smulOneHom_apply, smul_one_mul, smul_pow]
variable (R)
@[simp]
| Mathlib/Algebra/Polynomial/Smeval.lean | 79 | 80 | theorem smeval_zero : (0 : R[X]).smeval x = 0 := by | simp only [smeval_eq_sum, smul_pow, sum_zero_index] |
/-
Copyright (c) 2021 Eric Wieser. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Eric Wieser
-/
import Mathlib.GroupTheory.Perm.Cycle.Type
import Mathlib.GroupTheory.Perm.Option
import Mathlib.Logic.Equiv.Fin.Rotate
import Mathlib.Logic.Equiv.Fintype
/-!
# Permutations of `Fin n`
-/
assert_not_exists LinearMap
open Equiv
/-- Permutations of `Fin (n + 1)` are equivalent to fixing a single
`Fin (n + 1)` and permuting the remaining with a `Perm (Fin n)`.
The fixed `Fin (n + 1)` is swapped with `0`. -/
def Equiv.Perm.decomposeFin {n : ℕ} : Perm (Fin n.succ) ≃ Fin n.succ × Perm (Fin n) :=
((Equiv.permCongr <| finSuccEquiv n).trans Equiv.Perm.decomposeOption).trans
(Equiv.prodCongr (finSuccEquiv n).symm (Equiv.refl _))
@[simp]
theorem Equiv.Perm.decomposeFin_symm_of_refl {n : ℕ} (p : Fin (n + 1)) :
Equiv.Perm.decomposeFin.symm (p, Equiv.refl _) = swap 0 p := by
simp [Equiv.Perm.decomposeFin, Equiv.permCongr_def]
@[simp]
theorem Equiv.Perm.decomposeFin_symm_of_one {n : ℕ} (p : Fin (n + 1)) :
Equiv.Perm.decomposeFin.symm (p, 1) = swap 0 p :=
Equiv.Perm.decomposeFin_symm_of_refl p
@[simp]
theorem Equiv.Perm.decomposeFin_symm_apply_zero {n : ℕ} (p : Fin (n + 1)) (e : Perm (Fin n)) :
Equiv.Perm.decomposeFin.symm (p, e) 0 = p := by simp [Equiv.Perm.decomposeFin]
@[simp]
theorem Equiv.Perm.decomposeFin_symm_apply_succ {n : ℕ} (e : Perm (Fin n)) (p : Fin (n + 1))
(x : Fin n) : Equiv.Perm.decomposeFin.symm (p, e) x.succ = swap 0 p (e x).succ := by
refine Fin.cases ?_ ?_ p
· simp [Equiv.Perm.decomposeFin, EquivFunctor.map]
· intro i
by_cases h : i = e x
· simp [h, Equiv.Perm.decomposeFin, EquivFunctor.map]
· simp [h, Equiv.Perm.decomposeFin, EquivFunctor.map, swap_apply_def, Ne.symm h]
@[simp]
theorem Equiv.Perm.decomposeFin_symm_apply_one {n : ℕ} (e : Perm (Fin (n + 1))) (p : Fin (n + 2)) :
Equiv.Perm.decomposeFin.symm (p, e) 1 = swap 0 p (e 0).succ := by
rw [← Fin.succ_zero_eq_one, Equiv.Perm.decomposeFin_symm_apply_succ e p 0]
@[simp]
theorem Equiv.Perm.decomposeFin.symm_sign {n : ℕ} (p : Fin (n + 1)) (e : Perm (Fin n)) :
Perm.sign (Equiv.Perm.decomposeFin.symm (p, e)) = ite (p = 0) 1 (-1) * Perm.sign e := by
refine Fin.cases ?_ ?_ p <;> simp [Equiv.Perm.decomposeFin]
/-- The set of all permutations of `Fin (n + 1)` can be constructed by augmenting the set of
permutations of `Fin n` by each element of `Fin (n + 1)` in turn. -/
theorem Finset.univ_perm_fin_succ {n : ℕ} :
@Finset.univ (Perm <| Fin n.succ) _ =
(Finset.univ : Finset <| Fin n.succ × Perm (Fin n)).map
Equiv.Perm.decomposeFin.symm.toEmbedding :=
(Finset.univ_map_equiv_to_embedding _).symm
section CycleRange
/-! ### `cycleRange` section
Define the permutations `Fin.cycleRange i`, the cycle `(0 1 2 ... i)`.
-/
open Equiv.Perm
theorem finRotate_succ_eq_decomposeFin {n : ℕ} :
finRotate n.succ = decomposeFin.symm (1, finRotate n) := by
ext i
cases n; · simp
refine Fin.cases ?_ (fun i => ?_) i
· simp
rw [coe_finRotate, decomposeFin_symm_apply_succ, if_congr i.succ_eq_last_succ rfl rfl]
split_ifs with h
· simp [h]
· rw [Fin.val_succ, Function.Injective.map_swap Fin.val_injective, Fin.val_succ, coe_finRotate,
if_neg h, Fin.val_zero, Fin.val_one,
swap_apply_of_ne_of_ne (Nat.succ_ne_zero _) (Nat.succ_succ_ne_one _)]
@[simp]
theorem sign_finRotate (n : ℕ) : Perm.sign (finRotate (n + 1)) = (-1) ^ n := by
induction n with
| zero => simp
| succ n ih =>
rw [finRotate_succ_eq_decomposeFin]
simp [ih, pow_succ]
@[simp]
theorem support_finRotate {n : ℕ} : support (finRotate (n + 2)) = Finset.univ := by
ext
simp
theorem support_finRotate_of_le {n : ℕ} (h : 2 ≤ n) : support (finRotate n) = Finset.univ := by
obtain ⟨m, rfl⟩ := exists_add_of_le h
rw [add_comm, support_finRotate]
theorem isCycle_finRotate {n : ℕ} : IsCycle (finRotate (n + 2)) := by
refine ⟨0, by simp, fun x hx' => ⟨x, ?_⟩⟩
clear hx'
obtain ⟨x, hx⟩ := x
rw [zpow_natCast, Fin.ext_iff, Fin.val_mk]
induction' x with x ih; · rfl
rw [pow_succ', Perm.mul_apply, coe_finRotate_of_ne_last, ih (lt_trans x.lt_succ_self hx)]
rw [Ne, Fin.ext_iff, ih (lt_trans x.lt_succ_self hx), Fin.val_last]
exact ne_of_lt (Nat.lt_of_succ_lt_succ hx)
| Mathlib/GroupTheory/Perm/Fin.lean | 118 | 120 | theorem isCycle_finRotate_of_le {n : ℕ} (h : 2 ≤ n) : IsCycle (finRotate n) := by | obtain ⟨m, rfl⟩ := exists_add_of_le h
rw [add_comm] |
/-
Copyright (c) 2022 Alex J. Best. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alex J. Best, Yaël Dillies
-/
import Mathlib.Algebra.Order.Archimedean.Hom
import Mathlib.Algebra.Order.Group.Pointwise.CompleteLattice
/-!
# Conditionally complete linear ordered fields
This file shows that the reals are unique, or, more formally, given a type satisfying the common
axioms of the reals (field, conditionally complete, linearly ordered) that there is an isomorphism
preserving these properties to the reals. This is `LinearOrderedField.inducedOrderRingIso` for `ℚ`.
Moreover this isomorphism is unique.
We introduce definitions of conditionally complete linear ordered fields, and show all such are
archimedean. We also construct the natural map from a `LinearOrderedField` to such a field.
## Main definitions
* `ConditionallyCompleteLinearOrderedField`: A field satisfying the standard axiomatization of
the real numbers, being a Dedekind complete and linear ordered field.
* `LinearOrderedField.inducedMap`: A (unique) map from any archimedean linear ordered field to a
conditionally complete linear ordered field. Various bundlings are available.
## Main results
* `LinearOrderedField.uniqueOrderRingHom` : Uniqueness of `OrderRingHom`s from an archimedean
linear ordered field to a conditionally complete linear ordered field.
* `LinearOrderedField.uniqueOrderRingIso` : Uniqueness of `OrderRingIso`s between two
conditionally complete linearly ordered fields.
## References
* https://mathoverflow.net/questions/362991/
who-first-characterized-the-real-numbers-as-the-unique-complete-ordered-field
## Tags
reals, conditionally complete, ordered field, uniqueness
-/
variable {F α β γ : Type*}
noncomputable section
open Function Rat Set
open scoped Pointwise
/-- A field which is both linearly ordered and conditionally complete with respect to the order.
This axiomatizes the reals. -/
-- @[protect_proj] -- Porting note: does not exist anymore
class ConditionallyCompleteLinearOrderedField (α : Type*) extends
Field α, ConditionallyCompleteLinearOrder α where
-- extends `IsStrictOrderedRing α` produces
-- (kernel) declaration has free variables
-- 'ConditionallyCompleteLinearOrderedField.toIsStrictOrderedRing'
[toIsStrictOrderedRing : IsStrictOrderedRing α]
attribute [instance] ConditionallyCompleteLinearOrderedField.toIsStrictOrderedRing
-- see Note [lower instance priority]
/-- Any conditionally complete linearly ordered field is archimedean. -/
instance (priority := 100) ConditionallyCompleteLinearOrderedField.to_archimedean
[ConditionallyCompleteLinearOrderedField α] : Archimedean α :=
archimedean_iff_nat_lt.2
(by
by_contra! h
obtain ⟨x, h⟩ := h
have := csSup_le (range_nonempty Nat.cast)
(forall_mem_range.2 fun m =>
le_sub_iff_add_le.2 <| le_csSup ⟨x, forall_mem_range.2 h⟩ ⟨m+1, Nat.cast_succ m⟩)
linarith)
namespace LinearOrderedField
/-!
### Rational cut map
The idea is that a conditionally complete linear ordered field is fully characterized by its copy of
the rationals. Hence we define `LinearOrderedField.cutMap β : α → Set β` which sends `a : α` to the
"rationals in `β`" that are less than `a`.
-/
section CutMap
variable [Field α] [LinearOrder α]
section DivisionRing
variable (β) [DivisionRing β] {a a₁ a₂ : α} {b : β} {q : ℚ}
/-- The lower cut of rationals inside a linear ordered field that are less than a given element of
another linear ordered field. -/
def cutMap (a : α) : Set β :=
(Rat.cast : ℚ → β) '' {t | ↑t < a}
theorem cutMap_mono (h : a₁ ≤ a₂) : cutMap β a₁ ⊆ cutMap β a₂ := image_subset _ fun _ => h.trans_lt'
variable {β}
@[simp]
theorem mem_cutMap_iff : b ∈ cutMap β a ↔ ∃ q : ℚ, (q : α) < a ∧ (q : β) = b := Iff.rfl
theorem coe_mem_cutMap_iff [CharZero β] : (q : β) ∈ cutMap β a ↔ (q : α) < a :=
Rat.cast_injective.mem_set_image
theorem cutMap_self (a : α) : cutMap α a = Iio a ∩ range (Rat.cast : ℚ → α) := by
ext
constructor
· rintro ⟨q, h, rfl⟩
exact ⟨h, q, rfl⟩
· rintro ⟨h, q, rfl⟩
exact ⟨q, h, rfl⟩
end DivisionRing
variable (β) [IsStrictOrderedRing α] [Field β] [LinearOrder β] [IsStrictOrderedRing β]
{a a₁ a₂ : α} {b : β} {q : ℚ}
theorem cutMap_coe (q : ℚ) : cutMap β (q : α) = Rat.cast '' {r : ℚ | (r : β) < q} := by
simp_rw [cutMap, Rat.cast_lt]
variable [Archimedean α]
omit [LinearOrder β] [IsStrictOrderedRing β] in
theorem cutMap_nonempty (a : α) : (cutMap β a).Nonempty :=
Nonempty.image _ <| exists_rat_lt a
theorem cutMap_bddAbove (a : α) : BddAbove (cutMap β a) := by
obtain ⟨q, hq⟩ := exists_rat_gt a
exact ⟨q, forall_mem_image.2 fun r hr => mod_cast (hq.trans' hr).le⟩
theorem cutMap_add (a b : α) : cutMap β (a + b) = cutMap β a + cutMap β b := by
refine (image_subset_iff.2 fun q hq => ?_).antisymm ?_
· rw [mem_setOf_eq, ← sub_lt_iff_lt_add] at hq
obtain ⟨q₁, hq₁q, hq₁ab⟩ := exists_rat_btwn hq
refine ⟨q₁, by rwa [coe_mem_cutMap_iff], q - q₁, ?_, add_sub_cancel _ _⟩
norm_cast
rw [coe_mem_cutMap_iff]
exact mod_cast sub_lt_comm.mp hq₁q
· rintro _ ⟨_, ⟨qa, ha, rfl⟩, _, ⟨qb, hb, rfl⟩, rfl⟩
-- After https://github.com/leanprover/lean4/pull/2734, `norm_cast` needs help with beta reduction.
refine ⟨qa + qb, ?_, by beta_reduce; norm_cast⟩
rw [mem_setOf_eq, cast_add]
exact add_lt_add ha hb
end CutMap
/-!
### Induced map
`LinearOrderedField.cutMap` spits out a `Set β`. To get something in `β`, we now take the supremum.
-/
section InducedMap
variable (α β γ) [Field α] [LinearOrder α] [IsStrictOrderedRing α]
[ConditionallyCompleteLinearOrderedField β] [ConditionallyCompleteLinearOrderedField γ]
/-- The induced order preserving function from a linear ordered field to a conditionally complete
linear ordered field, defined by taking the Sup in the codomain of all the rationals less than the
input. -/
def inducedMap (x : α) : β :=
sSup <| cutMap β x
variable [Archimedean α]
theorem inducedMap_mono : Monotone (inducedMap α β) := fun _ _ h =>
csSup_le_csSup (cutMap_bddAbove β _) (cutMap_nonempty β _) (cutMap_mono β h)
theorem inducedMap_rat (q : ℚ) : inducedMap α β (q : α) = q := by
refine csSup_eq_of_forall_le_of_forall_lt_exists_gt
(cutMap_nonempty β (q : α)) (fun x h => ?_) fun w h => ?_
· rw [cutMap_coe] at h
obtain ⟨r, h, rfl⟩ := h
exact le_of_lt h
· obtain ⟨q', hwq, hq⟩ := exists_rat_btwn h
rw [cutMap_coe]
exact ⟨q', ⟨_, hq, rfl⟩, hwq⟩
@[simp]
theorem inducedMap_zero : inducedMap α β 0 = 0 := mod_cast inducedMap_rat α β 0
@[simp]
theorem inducedMap_one : inducedMap α β 1 = 1 := mod_cast inducedMap_rat α β 1
variable {α β} {a : α} {b : β} {q : ℚ}
theorem inducedMap_nonneg (ha : 0 ≤ a) : 0 ≤ inducedMap α β a :=
(inducedMap_zero α _).ge.trans <| inducedMap_mono _ _ ha
theorem coe_lt_inducedMap_iff : (q : β) < inducedMap α β a ↔ (q : α) < a := by
refine ⟨fun h => ?_, fun hq => ?_⟩
· rw [← inducedMap_rat α] at h
exact (inducedMap_mono α β).reflect_lt h
· obtain ⟨q', hq, hqa⟩ := exists_rat_btwn hq
apply lt_csSup_of_lt (cutMap_bddAbove β a) (coe_mem_cutMap_iff.mpr hqa)
exact mod_cast hq
theorem lt_inducedMap_iff : b < inducedMap α β a ↔ ∃ q : ℚ, b < q ∧ (q : α) < a :=
⟨fun h => (exists_rat_btwn h).imp fun _ => And.imp_right coe_lt_inducedMap_iff.1,
fun ⟨q, hbq, hqa⟩ => hbq.trans <| by rwa [coe_lt_inducedMap_iff]⟩
@[simp]
theorem inducedMap_self (b : β) : inducedMap β β b = b :=
eq_of_forall_rat_lt_iff_lt fun _ => coe_lt_inducedMap_iff
variable (α β)
@[simp]
| Mathlib/Algebra/Order/CompleteField.lean | 216 | 222 | theorem inducedMap_inducedMap (a : α) : inducedMap β γ (inducedMap α β a) = inducedMap α γ a :=
eq_of_forall_rat_lt_iff_lt fun q => by
rw [coe_lt_inducedMap_iff, coe_lt_inducedMap_iff, Iff.comm, coe_lt_inducedMap_iff]
theorem inducedMap_inv_self (b : β) : inducedMap γ β (inducedMap β γ b) = b := by | rw [inducedMap_inducedMap, inducedMap_self] |
/-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.LinearAlgebra.AffineSpace.Basis
import Mathlib.LinearAlgebra.Matrix.NonsingularInverse
/-!
# Matrix results for barycentric co-ordinates
Results about the matrix of barycentric co-ordinates for a family of points in an affine space, with
respect to some affine basis.
-/
open Affine Matrix
open Set
universe u₁ u₂ u₃ u₄
variable {ι : Type u₁} {k : Type u₂} {V : Type u₃} {P : Type u₄}
variable [AddCommGroup V] [AffineSpace V P]
namespace AffineBasis
section Ring
variable [Ring k] [Module k V] (b : AffineBasis ι k P)
/-- Given an affine basis `p`, and a family of points `q : ι' → P`, this is the matrix whose
rows are the barycentric coordinates of `q` with respect to `p`.
It is an affine equivalent of `Basis.toMatrix`. -/
noncomputable def toMatrix {ι' : Type*} (q : ι' → P) : Matrix ι' ι k :=
fun i j => b.coord j (q i)
@[simp]
theorem toMatrix_apply {ι' : Type*} (q : ι' → P) (i : ι') (j : ι) :
b.toMatrix q i j = b.coord j (q i) := rfl
@[simp]
theorem toMatrix_self [DecidableEq ι] : b.toMatrix b = (1 : Matrix ι ι k) := by
ext i j
rw [toMatrix_apply, coord_apply, Matrix.one_eq_pi_single, Pi.single_apply]
variable {ι' : Type*}
theorem toMatrix_row_sum_one [Fintype ι] (q : ι' → P) (i : ι') : ∑ j, b.toMatrix q i j = 1 := by
simp
/-- Given a family of points `p : ι' → P` and an affine basis `b`, if the matrix whose rows are the
coordinates of `p` with respect `b` has a right inverse, then `p` is affine independent. -/
theorem affineIndependent_of_toMatrix_right_inv [Fintype ι] [Finite ι'] [DecidableEq ι']
(p : ι' → P) {A : Matrix ι ι' k} (hA : b.toMatrix p * A = 1) : AffineIndependent k p := by
cases nonempty_fintype ι'
rw [affineIndependent_iff_eq_of_fintype_affineCombination_eq]
intro w₁ w₂ hw₁ hw₂ hweq
have hweq' : w₁ ᵥ* b.toMatrix p = w₂ ᵥ* b.toMatrix p := by
ext j
change (∑ i, w₁ i • b.coord j (p i)) = ∑ i, w₂ i • b.coord j (p i)
rw [← Finset.univ.affineCombination_eq_linear_combination _ _ hw₁,
← Finset.univ.affineCombination_eq_linear_combination _ _ hw₂,
← Function.comp_def (b.coord j) p, ← Finset.univ.map_affineCombination p w₁ hw₁,
← Finset.univ.map_affineCombination p w₂ hw₂, hweq]
replace hweq' := congr_arg (fun w => w ᵥ* A) hweq'
simpa only [Matrix.vecMul_vecMul, hA, Matrix.vecMul_one] using hweq'
/-- Given a family of points `p : ι' → P` and an affine basis `b`, if the matrix whose rows are the
coordinates of `p` with respect `b` has a left inverse, then `p` spans the entire space. -/
theorem affineSpan_eq_top_of_toMatrix_left_inv [Finite ι] [Fintype ι'] [DecidableEq ι]
[Nontrivial k] (p : ι' → P) {A : Matrix ι ι' k} (hA : A * b.toMatrix p = 1) :
affineSpan k (range p) = ⊤ := by
cases nonempty_fintype ι
suffices ∀ i, b i ∈ affineSpan k (range p) by
rw [eq_top_iff, ← b.tot, affineSpan_le]
rintro q ⟨i, rfl⟩
exact this i
intro i
have hAi : ∑ j, A i j = 1 := by
calc
∑ j, A i j = ∑ j, A i j * ∑ l, b.toMatrix p j l := by simp
_ = ∑ j, ∑ l, A i j * b.toMatrix p j l := by simp_rw [Finset.mul_sum]
_ = ∑ l, ∑ j, A i j * b.toMatrix p j l := by rw [Finset.sum_comm]
_ = ∑ l, (A * b.toMatrix p) i l := rfl
_ = 1 := by simp [hA, Matrix.one_apply, Finset.filter_eq]
have hbi : b i = Finset.univ.affineCombination k p (A i) := by
apply b.ext_elem
intro j
rw [b.coord_apply, Finset.univ.map_affineCombination _ _ hAi,
Finset.univ.affineCombination_eq_linear_combination _ _ hAi]
change _ = (A * b.toMatrix p) i j
simp_rw [hA, Matrix.one_apply, @eq_comm _ i j]
rw [hbi]
exact affineCombination_mem_affineSpan hAi p
variable [Fintype ι] (b₂ : AffineBasis ι k P)
/-- A change of basis formula for barycentric coordinates.
See also `AffineBasis.toMatrix_inv_vecMul_toMatrix`. -/
@[simp]
theorem toMatrix_vecMul_coords (x : P) : b₂.coords x ᵥ* b.toMatrix b₂ = b.coords x := by
ext j
change _ = b.coord j x
conv_rhs => rw [← b₂.affineCombination_coord_eq_self x]
rw [Finset.map_affineCombination _ _ _ (b₂.sum_coord_apply_eq_one x)]
simp [Matrix.vecMul, dotProduct, toMatrix_apply, coords]
variable [DecidableEq ι]
theorem toMatrix_mul_toMatrix : b.toMatrix b₂ * b₂.toMatrix b = 1 := by
ext l m
change (b.coords (b₂ l) ᵥ* b₂.toMatrix b) m = _
rw [toMatrix_vecMul_coords, coords_apply, ← toMatrix_apply, toMatrix_self]
theorem isUnit_toMatrix : IsUnit (b.toMatrix b₂) :=
⟨{ val := b.toMatrix b₂
inv := b₂.toMatrix b
val_inv := b.toMatrix_mul_toMatrix b₂
inv_val := b₂.toMatrix_mul_toMatrix b }, rfl⟩
| Mathlib/LinearAlgebra/AffineSpace/Matrix.lean | 124 | 127 | theorem isUnit_toMatrix_iff [Nontrivial k] (p : ι → P) :
IsUnit (b.toMatrix p) ↔ AffineIndependent k p ∧ affineSpan k (range p) = ⊤ := by | constructor
· rintro ⟨⟨B, A, hA, hA'⟩, rfl : B = b.toMatrix p⟩ |
/-
Copyright (c) 2020 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa
-/
import Mathlib.Algebra.Polynomial.Degree.TrailingDegree
import Mathlib.Algebra.Polynomial.EraseLead
/-!
# Reverse of a univariate polynomial
The main definition is `reverse`. Applying `reverse` to a polynomial `f : R[X]` produces
the polynomial with a reversed list of coefficients, equivalent to `X^f.natDegree * f(1/X)`.
The main result is that `reverse (f * g) = reverse f * reverse g`, provided the leading
coefficients of `f` and `g` do not multiply to zero.
-/
namespace Polynomial
open Finsupp Finset
open scoped Polynomial
section Semiring
variable {R : Type*} [Semiring R] {f : R[X]}
/-- If `i ≤ N`, then `revAtFun N i` returns `N - i`, otherwise it returns `i`.
This is the map used by the embedding `revAt`.
-/
def revAtFun (N i : ℕ) : ℕ :=
ite (i ≤ N) (N - i) i
theorem revAtFun_invol {N i : ℕ} : revAtFun N (revAtFun N i) = i := by
unfold revAtFun
split_ifs with h j
· exact tsub_tsub_cancel_of_le h
· exfalso
apply j
exact Nat.sub_le N i
· rfl
theorem revAtFun_inj {N : ℕ} : Function.Injective (revAtFun N) := by
intro a b hab
rw [← @revAtFun_invol N a, hab, revAtFun_invol]
/-- If `i ≤ N`, then `revAt N i` returns `N - i`, otherwise it returns `i`.
Essentially, this embedding is only used for `i ≤ N`.
The advantage of `revAt N i` over `N - i` is that `revAt` is an involution.
-/
def revAt (N : ℕ) : Function.Embedding ℕ ℕ where
toFun i := ite (i ≤ N) (N - i) i
inj' := revAtFun_inj
/-- We prefer to use the bundled `revAt` over unbundled `revAtFun`. -/
@[simp]
theorem revAtFun_eq (N i : ℕ) : revAtFun N i = revAt N i :=
rfl
@[simp]
theorem revAt_invol {N i : ℕ} : (revAt N) (revAt N i) = i :=
revAtFun_invol
@[simp]
theorem revAt_le {N i : ℕ} (H : i ≤ N) : revAt N i = N - i :=
if_pos H
lemma revAt_eq_self_of_lt {N i : ℕ} (h : N < i) : revAt N i = i := by simp [revAt, Nat.not_le.mpr h]
theorem revAt_add {N O n o : ℕ} (hn : n ≤ N) (ho : o ≤ O) :
revAt (N + O) (n + o) = revAt N n + revAt O o := by
rcases Nat.le.dest hn with ⟨n', rfl⟩
rcases Nat.le.dest ho with ⟨o', rfl⟩
repeat' rw [revAt_le (le_add_right rfl.le)]
rw [add_assoc, add_left_comm n' o, ← add_assoc, revAt_le (le_add_right rfl.le)]
repeat' rw [add_tsub_cancel_left]
| Mathlib/Algebra/Polynomial/Reverse.lean | 80 | 80 | theorem revAt_zero (N : ℕ) : revAt N 0 = N := by | simp |
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers, Heather Macbeth
-/
import Mathlib.Analysis.InnerProductSpace.TwoDim
import Mathlib.Geometry.Euclidean.Angle.Unoriented.Basic
/-!
# Oriented angles.
This file defines oriented angles in real inner product spaces.
## Main definitions
* `Orientation.oangle` is the oriented angle between two vectors with respect to an orientation.
## Implementation notes
The definitions here use the `Real.angle` type, angles modulo `2 * π`. For some purposes,
angles modulo `π` are more convenient, because results are true for such angles with less
configuration dependence. Results that are only equalities modulo `π` can be represented
modulo `2 * π` as equalities of `(2 : ℤ) • θ`.
## References
* Evan Chen, Euclidean Geometry in Mathematical Olympiads.
-/
noncomputable section
open Module Complex
open scoped Real RealInnerProductSpace ComplexConjugate
namespace Orientation
attribute [local instance] Complex.finrank_real_complex_fact
variable {V V' : Type*}
variable [NormedAddCommGroup V] [NormedAddCommGroup V']
variable [InnerProductSpace ℝ V] [InnerProductSpace ℝ V']
variable [Fact (finrank ℝ V = 2)] [Fact (finrank ℝ V' = 2)] (o : Orientation ℝ V (Fin 2))
local notation "ω" => o.areaForm
/-- The oriented angle from `x` to `y`, modulo `2 * π`. If either vector is 0, this is 0.
See `InnerProductGeometry.angle` for the corresponding unoriented angle definition. -/
def oangle (x y : V) : Real.Angle :=
Complex.arg (o.kahler x y)
/-- Oriented angles are continuous when the vectors involved are nonzero. -/
@[fun_prop]
theorem continuousAt_oangle {x : V × V} (hx1 : x.1 ≠ 0) (hx2 : x.2 ≠ 0) :
ContinuousAt (fun y : V × V => o.oangle y.1 y.2) x := by
refine (Complex.continuousAt_arg_coe_angle ?_).comp ?_
· exact o.kahler_ne_zero hx1 hx2
exact ((continuous_ofReal.comp continuous_inner).add
((continuous_ofReal.comp o.areaForm'.continuous₂).mul continuous_const)).continuousAt
/-- If the first vector passed to `oangle` is 0, the result is 0. -/
@[simp]
theorem oangle_zero_left (x : V) : o.oangle 0 x = 0 := by simp [oangle]
/-- If the second vector passed to `oangle` is 0, the result is 0. -/
@[simp]
theorem oangle_zero_right (x : V) : o.oangle x 0 = 0 := by simp [oangle]
/-- If the two vectors passed to `oangle` are the same, the result is 0. -/
@[simp]
theorem oangle_self (x : V) : o.oangle x x = 0 := by
rw [oangle, kahler_apply_self, ← ofReal_pow]
convert QuotientAddGroup.mk_zero (AddSubgroup.zmultiples (2 * π))
apply arg_ofReal_of_nonneg
positivity
/-- If the angle between two vectors is nonzero, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_ne_zero {x y : V} (h : o.oangle x y ≠ 0) : x ≠ 0 := by
rintro rfl; simp at h
/-- If the angle between two vectors is nonzero, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_ne_zero {x y : V} (h : o.oangle x y ≠ 0) : y ≠ 0 := by
rintro rfl; simp at h
/-- If the angle between two vectors is nonzero, the vectors are not equal. -/
theorem ne_of_oangle_ne_zero {x y : V} (h : o.oangle x y ≠ 0) : x ≠ y := by
rintro rfl; simp at h
/-- If the angle between two vectors is `π`, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_eq_pi {x y : V} (h : o.oangle x y = π) : x ≠ 0 :=
o.left_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `π`, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_eq_pi {x y : V} (h : o.oangle x y = π) : y ≠ 0 :=
o.right_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `π`, the vectors are not equal. -/
theorem ne_of_oangle_eq_pi {x y : V} (h : o.oangle x y = π) : x ≠ y :=
o.ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `π / 2`, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = (π / 2 : ℝ)) : x ≠ 0 :=
o.left_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `π / 2`, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = (π / 2 : ℝ)) : y ≠ 0 :=
o.right_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `π / 2`, the vectors are not equal. -/
theorem ne_of_oangle_eq_pi_div_two {x y : V} (h : o.oangle x y = (π / 2 : ℝ)) : x ≠ y :=
o.ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `-π / 2`, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_eq_neg_pi_div_two {x y : V} (h : o.oangle x y = (-π / 2 : ℝ)) :
x ≠ 0 :=
o.left_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `-π / 2`, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_eq_neg_pi_div_two {x y : V} (h : o.oangle x y = (-π / 2 : ℝ)) :
y ≠ 0 :=
o.right_ne_zero_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the angle between two vectors is `-π / 2`, the vectors are not equal. -/
theorem ne_of_oangle_eq_neg_pi_div_two {x y : V} (h : o.oangle x y = (-π / 2 : ℝ)) : x ≠ y :=
o.ne_of_oangle_ne_zero (h.symm ▸ Real.Angle.neg_pi_div_two_ne_zero : o.oangle x y ≠ 0)
/-- If the sign of the angle between two vectors is nonzero, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_sign_ne_zero {x y : V} (h : (o.oangle x y).sign ≠ 0) : x ≠ 0 :=
o.left_ne_zero_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1
/-- If the sign of the angle between two vectors is nonzero, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_sign_ne_zero {x y : V} (h : (o.oangle x y).sign ≠ 0) : y ≠ 0 :=
o.right_ne_zero_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1
/-- If the sign of the angle between two vectors is nonzero, the vectors are not equal. -/
theorem ne_of_oangle_sign_ne_zero {x y : V} (h : (o.oangle x y).sign ≠ 0) : x ≠ y :=
o.ne_of_oangle_ne_zero (Real.Angle.sign_ne_zero_iff.1 h).1
/-- If the sign of the angle between two vectors is positive, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_sign_eq_one {x y : V} (h : (o.oangle x y).sign = 1) : x ≠ 0 :=
o.left_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- If the sign of the angle between two vectors is positive, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_sign_eq_one {x y : V} (h : (o.oangle x y).sign = 1) : y ≠ 0 :=
o.right_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- If the sign of the angle between two vectors is positive, the vectors are not equal. -/
theorem ne_of_oangle_sign_eq_one {x y : V} (h : (o.oangle x y).sign = 1) : x ≠ y :=
o.ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- If the sign of the angle between two vectors is negative, the first vector is nonzero. -/
theorem left_ne_zero_of_oangle_sign_eq_neg_one {x y : V} (h : (o.oangle x y).sign = -1) : x ≠ 0 :=
o.left_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- If the sign of the angle between two vectors is negative, the second vector is nonzero. -/
theorem right_ne_zero_of_oangle_sign_eq_neg_one {x y : V} (h : (o.oangle x y).sign = -1) : y ≠ 0 :=
o.right_ne_zero_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- If the sign of the angle between two vectors is negative, the vectors are not equal. -/
theorem ne_of_oangle_sign_eq_neg_one {x y : V} (h : (o.oangle x y).sign = -1) : x ≠ y :=
o.ne_of_oangle_sign_ne_zero (h.symm ▸ by decide : (o.oangle x y).sign ≠ 0)
/-- Swapping the two vectors passed to `oangle` negates the angle. -/
theorem oangle_rev (x y : V) : o.oangle y x = -o.oangle x y := by
simp only [oangle, o.kahler_swap y x, Complex.arg_conj_coe_angle]
/-- Adding the angles between two vectors in each order results in 0. -/
@[simp]
theorem oangle_add_oangle_rev (x y : V) : o.oangle x y + o.oangle y x = 0 := by
simp [o.oangle_rev y x]
/-- Negating the first vector passed to `oangle` adds `π` to the angle. -/
theorem oangle_neg_left {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) :
o.oangle (-x) y = o.oangle x y + π := by
simp only [oangle, map_neg]
convert Complex.arg_neg_coe_angle _
exact o.kahler_ne_zero hx hy
/-- Negating the second vector passed to `oangle` adds `π` to the angle. -/
theorem oangle_neg_right {x y : V} (hx : x ≠ 0) (hy : y ≠ 0) :
o.oangle x (-y) = o.oangle x y + π := by
simp only [oangle, map_neg]
convert Complex.arg_neg_coe_angle _
exact o.kahler_ne_zero hx hy
/-- Negating the first vector passed to `oangle` does not change twice the angle. -/
@[simp]
theorem two_zsmul_oangle_neg_left (x y : V) :
(2 : ℤ) • o.oangle (-x) y = (2 : ℤ) • o.oangle x y := by
by_cases hx : x = 0
· simp [hx]
· by_cases hy : y = 0
· simp [hy]
· simp [o.oangle_neg_left hx hy]
/-- Negating the second vector passed to `oangle` does not change twice the angle. -/
@[simp]
theorem two_zsmul_oangle_neg_right (x y : V) :
(2 : ℤ) • o.oangle x (-y) = (2 : ℤ) • o.oangle x y := by
by_cases hx : x = 0
· simp [hx]
· by_cases hy : y = 0
· simp [hy]
· simp [o.oangle_neg_right hx hy]
/-- Negating both vectors passed to `oangle` does not change the angle. -/
@[simp]
theorem oangle_neg_neg (x y : V) : o.oangle (-x) (-y) = o.oangle x y := by simp [oangle]
/-- Negating the first vector produces the same angle as negating the second vector. -/
theorem oangle_neg_left_eq_neg_right (x y : V) : o.oangle (-x) y = o.oangle x (-y) := by
rw [← neg_neg y, oangle_neg_neg, neg_neg]
/-- The angle between the negation of a nonzero vector and that vector is `π`. -/
@[simp]
theorem oangle_neg_self_left {x : V} (hx : x ≠ 0) : o.oangle (-x) x = π := by
simp [oangle_neg_left, hx]
/-- The angle between a nonzero vector and its negation is `π`. -/
@[simp]
theorem oangle_neg_self_right {x : V} (hx : x ≠ 0) : o.oangle x (-x) = π := by
simp [oangle_neg_right, hx]
/-- Twice the angle between the negation of a vector and that vector is 0. -/
theorem two_zsmul_oangle_neg_self_left (x : V) : (2 : ℤ) • o.oangle (-x) x = 0 := by
by_cases hx : x = 0 <;> simp [hx]
/-- Twice the angle between a vector and its negation is 0. -/
theorem two_zsmul_oangle_neg_self_right (x : V) : (2 : ℤ) • o.oangle x (-x) = 0 := by
by_cases hx : x = 0 <;> simp [hx]
/-- Adding the angles between two vectors in each order, with the first vector in each angle
negated, results in 0. -/
@[simp]
theorem oangle_add_oangle_rev_neg_left (x y : V) : o.oangle (-x) y + o.oangle (-y) x = 0 := by
rw [oangle_neg_left_eq_neg_right, oangle_rev, neg_add_cancel]
/-- Adding the angles between two vectors in each order, with the second vector in each angle
negated, results in 0. -/
@[simp]
theorem oangle_add_oangle_rev_neg_right (x y : V) : o.oangle x (-y) + o.oangle y (-x) = 0 := by
rw [o.oangle_rev (-x), oangle_neg_left_eq_neg_right, add_neg_cancel]
/-- Multiplying the first vector passed to `oangle` by a positive real does not change the
angle. -/
@[simp]
theorem oangle_smul_left_of_pos (x y : V) {r : ℝ} (hr : 0 < r) :
o.oangle (r • x) y = o.oangle x y := by simp [oangle, Complex.arg_real_mul _ hr]
/-- Multiplying the second vector passed to `oangle` by a positive real does not change the
angle. -/
@[simp]
theorem oangle_smul_right_of_pos (x y : V) {r : ℝ} (hr : 0 < r) :
o.oangle x (r • y) = o.oangle x y := by simp [oangle, Complex.arg_real_mul _ hr]
/-- Multiplying the first vector passed to `oangle` by a negative real produces the same angle
as negating that vector. -/
@[simp]
theorem oangle_smul_left_of_neg (x y : V) {r : ℝ} (hr : r < 0) :
o.oangle (r • x) y = o.oangle (-x) y := by
rw [← neg_neg r, neg_smul, ← smul_neg, o.oangle_smul_left_of_pos _ _ (neg_pos_of_neg hr)]
/-- Multiplying the second vector passed to `oangle` by a negative real produces the same angle
as negating that vector. -/
@[simp]
theorem oangle_smul_right_of_neg (x y : V) {r : ℝ} (hr : r < 0) :
o.oangle x (r • y) = o.oangle x (-y) := by
rw [← neg_neg r, neg_smul, ← smul_neg, o.oangle_smul_right_of_pos _ _ (neg_pos_of_neg hr)]
/-- The angle between a nonnegative multiple of a vector and that vector is 0. -/
@[simp]
theorem oangle_smul_left_self_of_nonneg (x : V) {r : ℝ} (hr : 0 ≤ r) : o.oangle (r • x) x = 0 := by
rcases hr.lt_or_eq with (h | h)
· simp [h]
· simp [h.symm]
/-- The angle between a vector and a nonnegative multiple of that vector is 0. -/
@[simp]
theorem oangle_smul_right_self_of_nonneg (x : V) {r : ℝ} (hr : 0 ≤ r) : o.oangle x (r • x) = 0 := by
rcases hr.lt_or_eq with (h | h)
· simp [h]
· simp [h.symm]
/-- The angle between two nonnegative multiples of the same vector is 0. -/
@[simp]
theorem oangle_smul_smul_self_of_nonneg (x : V) {r₁ r₂ : ℝ} (hr₁ : 0 ≤ r₁) (hr₂ : 0 ≤ r₂) :
o.oangle (r₁ • x) (r₂ • x) = 0 := by
rcases hr₁.lt_or_eq with (h | h)
· simp [h, hr₂]
· simp [h.symm]
/-- Multiplying the first vector passed to `oangle` by a nonzero real does not change twice the
angle. -/
@[simp]
theorem two_zsmul_oangle_smul_left_of_ne_zero (x y : V) {r : ℝ} (hr : r ≠ 0) :
(2 : ℤ) • o.oangle (r • x) y = (2 : ℤ) • o.oangle x y := by
rcases hr.lt_or_lt with (h | h) <;> simp [h]
/-- Multiplying the second vector passed to `oangle` by a nonzero real does not change twice the
angle. -/
@[simp]
theorem two_zsmul_oangle_smul_right_of_ne_zero (x y : V) {r : ℝ} (hr : r ≠ 0) :
(2 : ℤ) • o.oangle x (r • y) = (2 : ℤ) • o.oangle x y := by
rcases hr.lt_or_lt with (h | h) <;> simp [h]
/-- Twice the angle between a multiple of a vector and that vector is 0. -/
@[simp]
theorem two_zsmul_oangle_smul_left_self (x : V) {r : ℝ} : (2 : ℤ) • o.oangle (r • x) x = 0 := by
rcases lt_or_le r 0 with (h | h) <;> simp [h]
/-- Twice the angle between a vector and a multiple of that vector is 0. -/
@[simp]
theorem two_zsmul_oangle_smul_right_self (x : V) {r : ℝ} : (2 : ℤ) • o.oangle x (r • x) = 0 := by
rcases lt_or_le r 0 with (h | h) <;> simp [h]
/-- Twice the angle between two multiples of a vector is 0. -/
@[simp]
theorem two_zsmul_oangle_smul_smul_self (x : V) {r₁ r₂ : ℝ} :
(2 : ℤ) • o.oangle (r₁ • x) (r₂ • x) = 0 := by by_cases h : r₁ = 0 <;> simp [h]
/-- If the spans of two vectors are equal, twice angles with those vectors on the left are
equal. -/
theorem two_zsmul_oangle_left_of_span_eq {x y : V} (z : V) (h : (ℝ ∙ x) = ℝ ∙ y) :
(2 : ℤ) • o.oangle x z = (2 : ℤ) • o.oangle y z := by
rw [Submodule.span_singleton_eq_span_singleton] at h
rcases h with ⟨r, rfl⟩
exact (o.two_zsmul_oangle_smul_left_of_ne_zero _ _ (Units.ne_zero _)).symm
/-- If the spans of two vectors are equal, twice angles with those vectors on the right are
equal. -/
theorem two_zsmul_oangle_right_of_span_eq (x : V) {y z : V} (h : (ℝ ∙ y) = ℝ ∙ z) :
(2 : ℤ) • o.oangle x y = (2 : ℤ) • o.oangle x z := by
rw [Submodule.span_singleton_eq_span_singleton] at h
rcases h with ⟨r, rfl⟩
exact (o.two_zsmul_oangle_smul_right_of_ne_zero _ _ (Units.ne_zero _)).symm
/-- If the spans of two pairs of vectors are equal, twice angles between those vectors are
equal. -/
theorem two_zsmul_oangle_of_span_eq_of_span_eq {w x y z : V} (hwx : (ℝ ∙ w) = ℝ ∙ x)
(hyz : (ℝ ∙ y) = ℝ ∙ z) : (2 : ℤ) • o.oangle w y = (2 : ℤ) • o.oangle x z := by
rw [o.two_zsmul_oangle_left_of_span_eq y hwx, o.two_zsmul_oangle_right_of_span_eq x hyz]
/-- The oriented angle between two vectors is zero if and only if the angle with the vectors
swapped is zero. -/
| Mathlib/Geometry/Euclidean/Angle/Oriented/Basic.lean | 347 | 349 | theorem oangle_eq_zero_iff_oangle_rev_eq_zero {x y : V} : o.oangle x y = 0 ↔ o.oangle y x = 0 := by | rw [oangle_rev, neg_eq_zero] |
/-
Copyright (c) 2024 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca, Pietro Monticone
-/
import Mathlib.NumberTheory.Cyclotomic.Embeddings
import Mathlib.NumberTheory.Cyclotomic.Rat
import Mathlib.NumberTheory.NumberField.Units.DirichletTheorem
import Mathlib.RingTheory.Fintype
/-!
# Third Cyclotomic Field
We gather various results about the third cyclotomic field. The following notations are used in this
file: `K` is a number field such that `IsCyclotomicExtension {3} ℚ K`, `ζ` is any primitive `3`-rd
root of unity in `K`, `η` is the element in the units of the ring of integers corresponding to `ζ`
and `λ = η - 1`.
## Main results
* `IsCyclotomicExtension.Rat.Three.Units.mem`: Given a unit `u : (𝓞 K)ˣ`, we have that
`u ∈ {1, -1, η, -η, η^2, -η^2}`.
* `IsCyclotomicExtension.Rat.Three.eq_one_or_neg_one_of_unit_of_congruent`: Given a unit
`u : (𝓞 K)ˣ`, if `u` is congruent to an integer modulo `3`, then `u = 1` or `u = -1`.
This is a special case of the so-called *Kummer's lemma* (see for example [washington_cyclotomic],
Theorem 5.36
-/
open NumberField Units InfinitePlace nonZeroDivisors Polynomial
namespace IsCyclotomicExtension.Rat.Three
variable {K : Type*} [Field K]
variable {ζ : K} (hζ : IsPrimitiveRoot ζ ↑(3 : ℕ+)) (u : (𝓞 K)ˣ)
local notation3 "η" => (IsPrimitiveRoot.isUnit (hζ.toInteger_isPrimitiveRoot) (by decide)).unit
local notation3 "λ" => hζ.toInteger - 1
lemma coe_eta : (η : 𝓞 K) = hζ.toInteger := rfl
lemma _root_.IsPrimitiveRoot.toInteger_cube_eq_one : hζ.toInteger ^ 3 = 1 :=
hζ.toInteger_isPrimitiveRoot.pow_eq_one
/-- Let `u` be a unit in `(𝓞 K)ˣ`, then `u ∈ [1, -1, η, -η, η^2, -η^2]`. -/
-- Here `List` is more convenient than `Finset`, even if further from the informal statement.
-- For example, `fin_cases` below does not work with a `Finset`.
| Mathlib/NumberTheory/Cyclotomic/Three.lean | 47 | 74 | theorem Units.mem [NumberField K] [IsCyclotomicExtension {3} ℚ K] :
u ∈ [1, -1, η, -η, η ^ 2, -η ^ 2] := by | have hrank : rank K = 0 := by
dsimp only [rank]
rw [card_eq_nrRealPlaces_add_nrComplexPlaces, nrRealPlaces_eq_zero (n := 3) K (by decide),
zero_add, nrComplexPlaces_eq_totient_div_two (n := 3)]
rfl
obtain ⟨⟨x, e⟩, hxu, -⟩ := exist_unique_eq_mul_prod _ u
replace hxu : u = x := by
rw [← mul_one x.1, hxu]
apply congr_arg
rw [← Finset.prod_empty]
congr
rw [Finset.univ_eq_empty_iff, hrank]
infer_instance
obtain ⟨n, hnpos, hn⟩ := isOfFinOrder_iff_pow_eq_one.1 <| (CommGroup.mem_torsion _ _).1 x.2
replace hn : (↑u : K) ^ ((⟨n, hnpos⟩ : ℕ+) : ℕ) = 1 := by
rw [← map_pow]
convert map_one (algebraMap (𝓞 K) K)
rw_mod_cast [hxu, hn]
simp
obtain ⟨r, hr3, hru⟩ := hζ.exists_pow_or_neg_mul_pow_of_isOfFinOrder (by decide)
(isOfFinOrder_iff_pow_eq_one.2 ⟨n, hnpos, hn⟩)
replace hr : r ∈ Finset.Ico 0 3 := Finset.mem_Ico.2 ⟨by simp, hr3⟩
replace hru : ↑u = η ^ r ∨ ↑u = -η ^ r := by
rcases hru with h | h
· left; ext; exact h
· right; ext; exact h |
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Patrick Massot, Casper Putz, Anne Baanen
-/
import Mathlib.Algebra.Algebra.Subalgebra.Tower
import Mathlib.Data.Finite.Sum
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.Notation
import Mathlib.LinearAlgebra.Basis.Basic
import Mathlib.LinearAlgebra.Basis.Fin
import Mathlib.LinearAlgebra.Basis.Prod
import Mathlib.LinearAlgebra.Basis.SMul
import Mathlib.LinearAlgebra.Matrix.StdBasis
import Mathlib.RingTheory.AlgebraTower
import Mathlib.RingTheory.Ideal.Span
/-!
# Linear maps and matrices
This file defines the maps to send matrices to a linear map,
and to send linear maps between modules with a finite bases
to matrices. This defines a linear equivalence between linear maps
between finite-dimensional vector spaces and matrices indexed by
the respective bases.
## Main definitions
In the list below, and in all this file, `R` is a commutative ring (semiring
is sometimes enough), `M` and its variations are `R`-modules, `ι`, `κ`, `n` and `m` are finite
types used for indexing.
* `LinearMap.toMatrix`: given bases `v₁ : ι → M₁` and `v₂ : κ → M₂`,
the `R`-linear equivalence from `M₁ →ₗ[R] M₂` to `Matrix κ ι R`
* `Matrix.toLin`: the inverse of `LinearMap.toMatrix`
* `LinearMap.toMatrix'`: the `R`-linear equivalence from `(m → R) →ₗ[R] (n → R)`
to `Matrix m n R` (with the standard basis on `m → R` and `n → R`)
* `Matrix.toLin'`: the inverse of `LinearMap.toMatrix'`
* `algEquivMatrix`: given a basis indexed by `n`, the `R`-algebra equivalence between
`R`-endomorphisms of `M` and `Matrix n n R`
## Issues
This file was originally written without attention to non-commutative rings,
and so mostly only works in the commutative setting. This should be fixed.
In particular, `Matrix.mulVec` gives us a linear equivalence
`Matrix m n R ≃ₗ[R] (n → R) →ₗ[Rᵐᵒᵖ] (m → R)`
while `Matrix.vecMul` gives us a linear equivalence
`Matrix m n R ≃ₗ[Rᵐᵒᵖ] (m → R) →ₗ[R] (n → R)`.
At present, the first equivalence is developed in detail but only for commutative rings
(and we omit the distinction between `Rᵐᵒᵖ` and `R`),
while the second equivalence is developed only in brief, but for not-necessarily-commutative rings.
Naming is slightly inconsistent between the two developments.
In the original (commutative) development `linear` is abbreviated to `lin`,
although this is not consistent with the rest of mathlib.
In the new (non-commutative) development `linear` is not abbreviated, and declarations use `_right`
to indicate they use the right action of matrices on vectors (via `Matrix.vecMul`).
When the two developments are made uniform, the names should be made uniform, too,
by choosing between `linear` and `lin` consistently,
and (presumably) adding `_left` where necessary.
## Tags
linear_map, matrix, linear_equiv, diagonal, det, trace
-/
noncomputable section
open LinearMap Matrix Set Submodule
section ToMatrixRight
variable {R : Type*} [Semiring R]
variable {l m n : Type*}
/-- `Matrix.vecMul M` is a linear map. -/
def Matrix.vecMulLinear [Fintype m] (M : Matrix m n R) : (m → R) →ₗ[R] n → R where
toFun x := x ᵥ* M
map_add' _ _ := funext fun _ ↦ add_dotProduct _ _ _
map_smul' _ _ := funext fun _ ↦ smul_dotProduct _ _ _
@[simp] theorem Matrix.vecMulLinear_apply [Fintype m] (M : Matrix m n R) (x : m → R) :
M.vecMulLinear x = x ᵥ* M := rfl
theorem Matrix.coe_vecMulLinear [Fintype m] (M : Matrix m n R) :
(M.vecMulLinear : _ → _) = M.vecMul := rfl
variable [Fintype m]
theorem range_vecMulLinear (M : Matrix m n R) :
LinearMap.range M.vecMulLinear = span R (range M.row) := by
letI := Classical.decEq m
simp_rw [range_eq_map, ← iSup_range_single, Submodule.map_iSup, range_eq_map, ←
Ideal.span_singleton_one, Ideal.span, Submodule.map_span, image_image, image_singleton,
Matrix.vecMulLinear_apply, iSup_span, range_eq_iUnion, iUnion_singleton_eq_range,
LinearMap.single, LinearMap.coe_mk, AddHom.coe_mk, row_def]
unfold vecMul
simp_rw [single_dotProduct, one_mul]
| Mathlib/LinearAlgebra/Matrix/ToLin.lean | 102 | 110 | theorem Matrix.vecMul_injective_iff {R : Type*} [Ring R] {M : Matrix m n R} :
Function.Injective M.vecMul ↔ LinearIndependent R M.row := by | rw [← coe_vecMulLinear]
simp only [← LinearMap.ker_eq_bot, Fintype.linearIndependent_iff, Submodule.eq_bot_iff,
LinearMap.mem_ker, vecMulLinear_apply, row_def]
refine ⟨fun h c h0 ↦ congr_fun <| h c ?_, fun h c h0 ↦ funext <| h c ?_⟩
· rw [← h0]
ext i
simp [vecMul, dotProduct] |
/-
Copyright (c) 2023 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Topology.Baire.Lemmas
import Mathlib.Topology.Algebra.Group.Pointwise
/-! # Open mapping theorem for morphisms of topological groups
We prove that a continuous surjective group morphism from a sigma-compact group to a locally compact
group is automatically open, in `MonoidHom.isOpenMap_of_sigmaCompact`.
We deduce this from a similar statement for the orbits of continuous actions of sigma-compact groups
on Baire spaces, given in `isOpenMap_smul_of_sigmaCompact`.
Note that a sigma-compactness assumption is necessary. Indeed, let `G` be the real line with
the discrete topology, and `H` the real line with the usual topology. Both are locally compact
groups, and the identity from `G` to `H` is continuous but not open.
-/
open scoped Topology Pointwise
open MulAction Set Function
variable {G X : Type*} [TopologicalSpace G] [TopologicalSpace X]
[Group G] [IsTopologicalGroup G] [MulAction G X]
[SigmaCompactSpace G] [BaireSpace X] [T2Space X]
[ContinuousSMul G X] [IsPretransitive G X]
/-- Consider a sigma-compact group acting continuously and transitively on a Baire space. Then
the orbit map is open around the identity. It follows in `isOpenMap_smul_of_sigmaCompact` that it
is open around any point. -/
@[to_additive "Consider a sigma-compact additive group acting continuously and transitively on a
Baire space. Then the orbit map is open around zero. It follows in
`isOpenMap_vadd_of_sigmaCompact` that it is open around any point."]
| Mathlib/Topology/Algebra/Group/OpenMapping.lean | 37 | 88 | theorem smul_singleton_mem_nhds_of_sigmaCompact
{U : Set G} (hU : U ∈ 𝓝 1) (x : X) : U • {x} ∈ 𝓝 x := by | /- Consider a small closed neighborhood `V` of the identity. Then the group is covered by
countably many translates of `V`, say `gᵢ V`. Let also `Kₙ` be a sequence of compact sets covering
the space. Then the image of `Kₙ ∩ gᵢ V` in the orbit is compact, and their unions covers the
space. By Baire, one of them has nonempty interior. Then `gᵢ V • x` has nonempty interior, and
so does `V • x`. Its interior contains a point `g' x` with `g' ∈ V`. Then `g'⁻¹ • V • x` contains
a neighborhood of `x`, and it is included in `V⁻¹ • V • x`, which is itself contained in `U • x`
if `V` is small enough. -/
obtain ⟨V, V_mem, V_closed, V_symm, VU⟩ : ∃ V ∈ 𝓝 (1 : G), IsClosed V ∧ V⁻¹ = V ∧ V * V ⊆ U :=
exists_closed_nhds_one_inv_eq_mul_subset hU
obtain ⟨s, s_count, hs⟩ : ∃ (s : Set G), s.Countable ∧ ⋃ g ∈ s, g • V = univ :=
countable_cover_nhds_of_sigmaCompact fun _ ↦ by simpa
let K : ℕ → Set G := compactCovering G
let F : ℕ × s → Set X := fun p ↦ (K p.1 ∩ (p.2 : G) • V) • ({x} : Set X)
obtain ⟨⟨n, ⟨g, hg⟩⟩, hi⟩ : ∃ i, (interior (F i)).Nonempty := by
have : Nonempty X := ⟨x⟩
have : Encodable s := Countable.toEncodable s_count
apply nonempty_interior_of_iUnion_of_closed
· rintro ⟨n, ⟨g, hg⟩⟩
apply IsCompact.isClosed
suffices H : IsCompact ((fun (g : G) ↦ g • x) '' (K n ∩ g • V)) by
simpa only [F, smul_singleton] using H
apply IsCompact.image
· exact (isCompact_compactCovering G n).inter_right (V_closed.smul g)
· exact continuous_id.smul continuous_const
· apply eq_univ_iff_forall.2 (fun y ↦ ?_)
obtain ⟨h, rfl⟩ : ∃ h, h • x = y := exists_smul_eq G x y
obtain ⟨n, hn⟩ : ∃ n, h ∈ K n := exists_mem_compactCovering h
obtain ⟨g, gs, hg⟩ : ∃ g ∈ s, h ∈ g • V := exists_set_mem_of_union_eq_top s _ hs _
simp only [F, smul_singleton, mem_iUnion, mem_image, mem_inter_iff, Prod.exists,
Subtype.exists, exists_prop]
exact ⟨n, g, gs, h, ⟨hn, hg⟩, rfl⟩
have I : (interior ((g • V) • {x})).Nonempty := by
apply hi.mono
apply interior_mono
exact smul_subset_smul_right inter_subset_right
obtain ⟨y, hy⟩ : (interior (V • ({x} : Set X))).Nonempty := by
rw [smul_assoc, interior_smul] at I
exact smul_set_nonempty.1 I
obtain ⟨g', hg', rfl⟩ : ∃ g' ∈ V, g' • x = y := by simpa using interior_subset hy
have J : (g' ⁻¹ • V) • {x} ∈ 𝓝 x := by
apply mem_interior_iff_mem_nhds.1
rwa [smul_assoc, interior_smul, mem_inv_smul_set_iff]
have : (g'⁻¹ • V) • {x} ⊆ U • ({x} : Set X) := by
apply smul_subset_smul_right
apply Subset.trans (smul_set_subset_smul (inv_mem_inv.2 hg')) ?_
rw [V_symm]
exact VU
exact Filter.mem_of_superset J this
/-- Consider a sigma-compact group acting continuously and transitively on a Baire space. Then |
/-
Copyright (c) 2022 Moritz Doll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Moritz Doll, Kalle Kytölä
-/
import Mathlib.Analysis.Normed.Module.Basic
import Mathlib.LinearAlgebra.SesquilinearForm
import Mathlib.Topology.Algebra.Module.WeakBilin
/-!
# Polar set
In this file we define the polar set. There are different notions of the polar, we will define the
*absolute polar*. The advantage over the real polar is that we can define the absolute polar for
any bilinear form `B : E →ₗ[𝕜] F →ₗ[𝕜] 𝕜`, where `𝕜` is a normed commutative ring and
`E` and `F` are modules over `𝕜`.
## Main definitions
* `LinearMap.polar`: The polar of a bilinear form `B : E →ₗ[𝕜] F →ₗ[𝕜] 𝕜`.
## Main statements
* `LinearMap.polar_eq_iInter`: The polar as an intersection.
* `LinearMap.subset_bipolar`: The polar is a subset of the bipolar.
* `LinearMap.polar_weak_closed`: The polar is closed in the weak topology induced by `B.flip`.
## References
* [H. H. Schaefer, *Topological Vector Spaces*][schaefer1966]
## Tags
polar
-/
variable {𝕜 E F : Type*}
open Topology
namespace LinearMap
section NormedRing
variable [NormedCommRing 𝕜] [AddCommMonoid E] [AddCommMonoid F]
variable [Module 𝕜 E] [Module 𝕜 F]
variable (B : E →ₗ[𝕜] F →ₗ[𝕜] 𝕜)
/-- The (absolute) polar of `s : Set E` is given by the set of all `y : F` such that `‖B x y‖ ≤ 1`
for all `x ∈ s`. -/
def polar (s : Set E) : Set F :=
{ y : F | ∀ x ∈ s, ‖B x y‖ ≤ 1 }
theorem polar_mem_iff (s : Set E) (y : F) : y ∈ B.polar s ↔ ∀ x ∈ s, ‖B x y‖ ≤ 1 :=
Iff.rfl
theorem polar_mem (s : Set E) (y : F) (hy : y ∈ B.polar s) : ∀ x ∈ s, ‖B x y‖ ≤ 1 :=
hy
theorem polar_eq_biInter_preimage (s : Set E) :
B.polar s = ⋂ x ∈ s, ((B x) ⁻¹' Metric.closedBall (0 : 𝕜) 1) := by aesop
theorem polar_isClosed (s : Set E) : IsClosed (X := WeakBilin B.flip) (B.polar s) := by
rw [polar_eq_biInter_preimage]
exact isClosed_biInter
fun _ _ ↦ Metric.isClosed_closedBall.preimage (WeakBilin.eval_continuous B.flip _)
@[simp]
theorem zero_mem_polar (s : Set E) : (0 : F) ∈ B.polar s := fun _ _ => by
simp only [map_zero, norm_zero, zero_le_one]
theorem polar_nonempty (s : Set E) : Set.Nonempty (B.polar s) := by
use 0
exact zero_mem_polar B s
theorem polar_eq_iInter {s : Set E} : B.polar s = ⋂ x ∈ s, { y : F | ‖B x y‖ ≤ 1 } := by
ext
simp only [polar_mem_iff, Set.mem_iInter, Set.mem_setOf_eq]
/-- The map `B.polar : Set E → Set F` forms an order-reversing Galois connection with
`B.flip.polar : Set F → Set E`. We use `OrderDual.toDual` and `OrderDual.ofDual` to express
that `polar` is order-reversing. -/
theorem polar_gc :
GaloisConnection (OrderDual.toDual ∘ B.polar) (B.flip.polar ∘ OrderDual.ofDual) := fun _ _ =>
⟨fun h _ hx _ hy => h hy _ hx, fun h _ hx _ hy => h hy _ hx⟩
@[simp]
theorem polar_iUnion {ι} {s : ι → Set E} : B.polar (⋃ i, s i) = ⋂ i, B.polar (s i) :=
B.polar_gc.l_iSup
@[simp]
theorem polar_union {s t : Set E} : B.polar (s ∪ t) = B.polar s ∩ B.polar t :=
B.polar_gc.l_sup
theorem polar_antitone : Antitone (B.polar : Set E → Set F) :=
B.polar_gc.monotone_l
@[simp]
theorem polar_empty : B.polar ∅ = Set.univ :=
B.polar_gc.l_bot
@[simp]
theorem polar_singleton {a : E} : B.polar {a} = { y | ‖B a y‖ ≤ 1 } := le_antisymm
(fun _ hy => hy _ rfl)
(fun y hy => (polar_mem_iff _ _ _).mp (fun _ hb => by rw [Set.mem_singleton_iff.mp hb]; exact hy))
theorem mem_polar_singleton {x : E} (y : F) : y ∈ B.polar {x} ↔ ‖B x y‖ ≤ 1 := by
simp only [polar_singleton, Set.mem_setOf_eq]
| Mathlib/Analysis/LocallyConvex/Polar.lean | 112 | 114 | theorem polar_zero : B.polar ({0} : Set E) = Set.univ := by | simp only [polar_singleton, map_zero, zero_apply, norm_zero, zero_le_one, Set.setOf_true] |
/-
Copyright (c) 2022 David Kurniadi Angdinata. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Kurniadi Angdinata
-/
import Mathlib.Algebra.Polynomial.Splits
import Mathlib.Tactic.IntervalCases
/-!
# Cubics and discriminants
This file defines cubic polynomials over a semiring and their discriminants over a splitting field.
## Main definitions
* `Cubic`: the structure representing a cubic polynomial.
* `Cubic.disc`: the discriminant of a cubic polynomial.
## Main statements
* `Cubic.disc_ne_zero_iff_roots_nodup`: the cubic discriminant is not equal to zero if and only if
the cubic has no duplicate roots.
## References
* https://en.wikipedia.org/wiki/Cubic_equation
* https://en.wikipedia.org/wiki/Discriminant
## Tags
cubic, discriminant, polynomial, root
-/
noncomputable section
/-- The structure representing a cubic polynomial. -/
@[ext]
structure Cubic (R : Type*) where
/-- The degree-3 coefficient -/
a : R
/-- The degree-2 coefficient -/
b : R
/-- The degree-1 coefficient -/
c : R
/-- The degree-0 coefficient -/
d : R
namespace Cubic
open Polynomial
variable {R S F K : Type*}
instance [Inhabited R] : Inhabited (Cubic R) :=
⟨⟨default, default, default, default⟩⟩
instance [Zero R] : Zero (Cubic R) :=
⟨⟨0, 0, 0, 0⟩⟩
section Basic
variable {P Q : Cubic R} {a b c d a' b' c' d' : R} [Semiring R]
/-- Convert a cubic polynomial to a polynomial. -/
def toPoly (P : Cubic R) : R[X] :=
C P.a * X ^ 3 + C P.b * X ^ 2 + C P.c * X + C P.d
theorem C_mul_prod_X_sub_C_eq [CommRing S] {w x y z : S} :
C w * (X - C x) * (X - C y) * (X - C z) =
toPoly ⟨w, w * -(x + y + z), w * (x * y + x * z + y * z), w * -(x * y * z)⟩ := by
simp only [toPoly, C_neg, C_add, C_mul]
ring1
theorem prod_X_sub_C_eq [CommRing S] {x y z : S} :
(X - C x) * (X - C y) * (X - C z) =
toPoly ⟨1, -(x + y + z), x * y + x * z + y * z, -(x * y * z)⟩ := by
rw [← one_mul <| X - C x, ← C_1, C_mul_prod_X_sub_C_eq, one_mul, one_mul, one_mul]
/-! ### Coefficients -/
section Coeff
private theorem coeffs : (∀ n > 3, P.toPoly.coeff n = 0) ∧ P.toPoly.coeff 3 = P.a ∧
P.toPoly.coeff 2 = P.b ∧ P.toPoly.coeff 1 = P.c ∧ P.toPoly.coeff 0 = P.d := by
simp only [toPoly, coeff_add, coeff_C, coeff_C_mul_X, coeff_C_mul_X_pow]
norm_num
intro n hn
repeat' rw [if_neg]
any_goals omega
repeat' rw [zero_add]
@[simp]
theorem coeff_eq_zero {n : ℕ} (hn : 3 < n) : P.toPoly.coeff n = 0 :=
coeffs.1 n hn
@[simp]
theorem coeff_eq_a : P.toPoly.coeff 3 = P.a :=
coeffs.2.1
@[simp]
theorem coeff_eq_b : P.toPoly.coeff 2 = P.b :=
coeffs.2.2.1
@[simp]
theorem coeff_eq_c : P.toPoly.coeff 1 = P.c :=
coeffs.2.2.2.1
@[simp]
theorem coeff_eq_d : P.toPoly.coeff 0 = P.d :=
coeffs.2.2.2.2
theorem a_of_eq (h : P.toPoly = Q.toPoly) : P.a = Q.a := by rw [← coeff_eq_a, h, coeff_eq_a]
theorem b_of_eq (h : P.toPoly = Q.toPoly) : P.b = Q.b := by rw [← coeff_eq_b, h, coeff_eq_b]
theorem c_of_eq (h : P.toPoly = Q.toPoly) : P.c = Q.c := by rw [← coeff_eq_c, h, coeff_eq_c]
theorem d_of_eq (h : P.toPoly = Q.toPoly) : P.d = Q.d := by rw [← coeff_eq_d, h, coeff_eq_d]
theorem toPoly_injective (P Q : Cubic R) : P.toPoly = Q.toPoly ↔ P = Q :=
⟨fun h ↦ Cubic.ext (a_of_eq h) (b_of_eq h) (c_of_eq h) (d_of_eq h), congr_arg toPoly⟩
theorem of_a_eq_zero (ha : P.a = 0) : P.toPoly = C P.b * X ^ 2 + C P.c * X + C P.d := by
rw [toPoly, ha, C_0, zero_mul, zero_add]
theorem of_a_eq_zero' : toPoly ⟨0, b, c, d⟩ = C b * X ^ 2 + C c * X + C d :=
of_a_eq_zero rfl
theorem of_b_eq_zero (ha : P.a = 0) (hb : P.b = 0) : P.toPoly = C P.c * X + C P.d := by
rw [of_a_eq_zero ha, hb, C_0, zero_mul, zero_add]
theorem of_b_eq_zero' : toPoly ⟨0, 0, c, d⟩ = C c * X + C d :=
of_b_eq_zero rfl rfl
theorem of_c_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) : P.toPoly = C P.d := by
rw [of_b_eq_zero ha hb, hc, C_0, zero_mul, zero_add]
theorem of_c_eq_zero' : toPoly ⟨0, 0, 0, d⟩ = C d :=
of_c_eq_zero rfl rfl rfl
theorem of_d_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) (hd : P.d = 0) :
P.toPoly = 0 := by
rw [of_c_eq_zero ha hb hc, hd, C_0]
theorem of_d_eq_zero' : (⟨0, 0, 0, 0⟩ : Cubic R).toPoly = 0 :=
of_d_eq_zero rfl rfl rfl rfl
theorem zero : (0 : Cubic R).toPoly = 0 :=
of_d_eq_zero'
theorem toPoly_eq_zero_iff (P : Cubic R) : P.toPoly = 0 ↔ P = 0 := by
rw [← zero, toPoly_injective]
private theorem ne_zero (h0 : P.a ≠ 0 ∨ P.b ≠ 0 ∨ P.c ≠ 0 ∨ P.d ≠ 0) : P.toPoly ≠ 0 := by
contrapose! h0
rw [(toPoly_eq_zero_iff P).mp h0]
exact ⟨rfl, rfl, rfl, rfl⟩
theorem ne_zero_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp ne_zero).1 ha
theorem ne_zero_of_b_ne_zero (hb : P.b ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp (or_imp.mp ne_zero).2).1 hb
theorem ne_zero_of_c_ne_zero (hc : P.c ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp (or_imp.mp (or_imp.mp ne_zero).2).2).1 hc
theorem ne_zero_of_d_ne_zero (hd : P.d ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp (or_imp.mp (or_imp.mp ne_zero).2).2).2 hd
@[simp]
theorem leadingCoeff_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly.leadingCoeff = P.a :=
leadingCoeff_cubic ha
@[simp]
theorem leadingCoeff_of_a_ne_zero' (ha : a ≠ 0) : (toPoly ⟨a, b, c, d⟩).leadingCoeff = a :=
leadingCoeff_of_a_ne_zero ha
@[simp]
theorem leadingCoeff_of_b_ne_zero (ha : P.a = 0) (hb : P.b ≠ 0) : P.toPoly.leadingCoeff = P.b := by
rw [of_a_eq_zero ha, leadingCoeff_quadratic hb]
@[simp]
theorem leadingCoeff_of_b_ne_zero' (hb : b ≠ 0) : (toPoly ⟨0, b, c, d⟩).leadingCoeff = b :=
leadingCoeff_of_b_ne_zero rfl hb
@[simp]
theorem leadingCoeff_of_c_ne_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c ≠ 0) :
P.toPoly.leadingCoeff = P.c := by
rw [of_b_eq_zero ha hb, leadingCoeff_linear hc]
@[simp]
theorem leadingCoeff_of_c_ne_zero' (hc : c ≠ 0) : (toPoly ⟨0, 0, c, d⟩).leadingCoeff = c :=
leadingCoeff_of_c_ne_zero rfl rfl hc
@[simp]
theorem leadingCoeff_of_c_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) :
P.toPoly.leadingCoeff = P.d := by
rw [of_c_eq_zero ha hb hc, leadingCoeff_C]
theorem leadingCoeff_of_c_eq_zero' : (toPoly ⟨0, 0, 0, d⟩).leadingCoeff = d :=
leadingCoeff_of_c_eq_zero rfl rfl rfl
theorem monic_of_a_eq_one (ha : P.a = 1) : P.toPoly.Monic := by
nontriviality R
rw [Monic, leadingCoeff_of_a_ne_zero (ha ▸ one_ne_zero), ha]
theorem monic_of_a_eq_one' : (toPoly ⟨1, b, c, d⟩).Monic :=
monic_of_a_eq_one rfl
theorem monic_of_b_eq_one (ha : P.a = 0) (hb : P.b = 1) : P.toPoly.Monic := by
nontriviality R
rw [Monic, leadingCoeff_of_b_ne_zero ha (hb ▸ one_ne_zero), hb]
theorem monic_of_b_eq_one' : (toPoly ⟨0, 1, c, d⟩).Monic :=
monic_of_b_eq_one rfl rfl
theorem monic_of_c_eq_one (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 1) : P.toPoly.Monic := by
nontriviality R
rw [Monic, leadingCoeff_of_c_ne_zero ha hb (hc ▸ one_ne_zero), hc]
theorem monic_of_c_eq_one' : (toPoly ⟨0, 0, 1, d⟩).Monic :=
monic_of_c_eq_one rfl rfl rfl
theorem monic_of_d_eq_one (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) (hd : P.d = 1) :
P.toPoly.Monic := by
rw [Monic, leadingCoeff_of_c_eq_zero ha hb hc, hd]
theorem monic_of_d_eq_one' : (toPoly ⟨0, 0, 0, 1⟩).Monic :=
monic_of_d_eq_one rfl rfl rfl rfl
end Coeff
/-! ### Degrees -/
section Degree
/-- The equivalence between cubic polynomials and polynomials of degree at most three. -/
@[simps]
def equiv : Cubic R ≃ { p : R[X] // p.degree ≤ 3 } where
toFun P := ⟨P.toPoly, degree_cubic_le⟩
invFun f := ⟨coeff f 3, coeff f 2, coeff f 1, coeff f 0⟩
left_inv P := by ext <;> simp only [Subtype.coe_mk, coeffs]
right_inv f := by
ext n
obtain hn | hn := le_or_lt n 3
· interval_cases n <;> simp only [Nat.succ_eq_add_one] <;> ring_nf <;> try simp only [coeffs]
· rw [coeff_eq_zero hn, (degree_le_iff_coeff_zero (f : R[X]) 3).mp f.2]
simpa using hn
@[simp]
theorem degree_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly.degree = 3 :=
degree_cubic ha
@[simp]
theorem degree_of_a_ne_zero' (ha : a ≠ 0) : (toPoly ⟨a, b, c, d⟩).degree = 3 :=
degree_of_a_ne_zero ha
theorem degree_of_a_eq_zero (ha : P.a = 0) : P.toPoly.degree ≤ 2 := by
simpa only [of_a_eq_zero ha] using degree_quadratic_le
theorem degree_of_a_eq_zero' : (toPoly ⟨0, b, c, d⟩).degree ≤ 2 :=
degree_of_a_eq_zero rfl
@[simp]
theorem degree_of_b_ne_zero (ha : P.a = 0) (hb : P.b ≠ 0) : P.toPoly.degree = 2 := by
rw [of_a_eq_zero ha, degree_quadratic hb]
@[simp]
theorem degree_of_b_ne_zero' (hb : b ≠ 0) : (toPoly ⟨0, b, c, d⟩).degree = 2 :=
degree_of_b_ne_zero rfl hb
theorem degree_of_b_eq_zero (ha : P.a = 0) (hb : P.b = 0) : P.toPoly.degree ≤ 1 := by
simpa only [of_b_eq_zero ha hb] using degree_linear_le
theorem degree_of_b_eq_zero' : (toPoly ⟨0, 0, c, d⟩).degree ≤ 1 :=
degree_of_b_eq_zero rfl rfl
@[simp]
theorem degree_of_c_ne_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c ≠ 0) : P.toPoly.degree = 1 := by
rw [of_b_eq_zero ha hb, degree_linear hc]
@[simp]
theorem degree_of_c_ne_zero' (hc : c ≠ 0) : (toPoly ⟨0, 0, c, d⟩).degree = 1 :=
degree_of_c_ne_zero rfl rfl hc
theorem degree_of_c_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) : P.toPoly.degree ≤ 0 := by
simpa only [of_c_eq_zero ha hb hc] using degree_C_le
theorem degree_of_c_eq_zero' : (toPoly ⟨0, 0, 0, d⟩).degree ≤ 0 :=
degree_of_c_eq_zero rfl rfl rfl
@[simp]
theorem degree_of_d_ne_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) (hd : P.d ≠ 0) :
P.toPoly.degree = 0 := by
rw [of_c_eq_zero ha hb hc, degree_C hd]
@[simp]
theorem degree_of_d_ne_zero' (hd : d ≠ 0) : (toPoly ⟨0, 0, 0, d⟩).degree = 0 :=
degree_of_d_ne_zero rfl rfl rfl hd
@[simp]
theorem degree_of_d_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) (hd : P.d = 0) :
P.toPoly.degree = ⊥ := by
rw [of_d_eq_zero ha hb hc hd, degree_zero]
theorem degree_of_d_eq_zero' : (⟨0, 0, 0, 0⟩ : Cubic R).toPoly.degree = ⊥ :=
degree_of_d_eq_zero rfl rfl rfl rfl
@[simp]
theorem degree_of_zero : (0 : Cubic R).toPoly.degree = ⊥ :=
degree_of_d_eq_zero'
@[simp]
theorem natDegree_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly.natDegree = 3 :=
natDegree_cubic ha
@[simp]
theorem natDegree_of_a_ne_zero' (ha : a ≠ 0) : (toPoly ⟨a, b, c, d⟩).natDegree = 3 :=
natDegree_of_a_ne_zero ha
theorem natDegree_of_a_eq_zero (ha : P.a = 0) : P.toPoly.natDegree ≤ 2 := by
simpa only [of_a_eq_zero ha] using natDegree_quadratic_le
theorem natDegree_of_a_eq_zero' : (toPoly ⟨0, b, c, d⟩).natDegree ≤ 2 :=
natDegree_of_a_eq_zero rfl
@[simp]
theorem natDegree_of_b_ne_zero (ha : P.a = 0) (hb : P.b ≠ 0) : P.toPoly.natDegree = 2 := by
rw [of_a_eq_zero ha, natDegree_quadratic hb]
@[simp]
theorem natDegree_of_b_ne_zero' (hb : b ≠ 0) : (toPoly ⟨0, b, c, d⟩).natDegree = 2 :=
natDegree_of_b_ne_zero rfl hb
theorem natDegree_of_b_eq_zero (ha : P.a = 0) (hb : P.b = 0) : P.toPoly.natDegree ≤ 1 := by
simpa only [of_b_eq_zero ha hb] using natDegree_linear_le
theorem natDegree_of_b_eq_zero' : (toPoly ⟨0, 0, c, d⟩).natDegree ≤ 1 :=
natDegree_of_b_eq_zero rfl rfl
@[simp]
| Mathlib/Algebra/CubicDiscriminant.lean | 346 | 347 | theorem natDegree_of_c_ne_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c ≠ 0) :
P.toPoly.natDegree = 1 := by | |
/-
Copyright (c) 2022 Moritz Doll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Moritz Doll
-/
import Mathlib.Analysis.InnerProductSpace.Adjoint
import Mathlib.Topology.Algebra.Module.Equiv
/-!
# Partially defined linear operators on Hilbert spaces
We will develop the basics of the theory of unbounded operators on Hilbert spaces.
## Main definitions
* `LinearPMap.IsFormalAdjoint`: An operator `T` is a formal adjoint of `S` if for all `x` in the
domain of `T` and `y` in the domain of `S`, we have that `⟪T x, y⟫ = ⟪x, S y⟫`.
* `LinearPMap.adjoint`: The adjoint of a map `E →ₗ.[𝕜] F` as a map `F →ₗ.[𝕜] E`.
## Main statements
* `LinearPMap.adjoint_isFormalAdjoint`: The adjoint is a formal adjoint
* `LinearPMap.IsFormalAdjoint.le_adjoint`: Every formal adjoint is contained in the adjoint
* `ContinuousLinearMap.toPMap_adjoint_eq_adjoint_toPMap_of_dense`: The adjoint on
`ContinuousLinearMap` and `LinearPMap` coincide.
## Notation
* For `T : E →ₗ.[𝕜] F` the adjoint can be written as `T†`.
This notation is localized in `LinearPMap`.
## Implementation notes
We use the junk value pattern to define the adjoint for all `LinearPMap`s. In the case that
`T : E →ₗ.[𝕜] F` is not densely defined the adjoint `T†` is the zero map from `T.adjoint.domain` to
`E`.
## References
* [J. Weidmann, *Linear Operators in Hilbert Spaces*][weidmann_linear]
## Tags
Unbounded operators, closed operators
-/
noncomputable section
open RCLike
open scoped ComplexConjugate
variable {𝕜 E F : Type*} [RCLike 𝕜]
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace 𝕜 F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
namespace LinearPMap
/-- An operator `T` is a formal adjoint of `S` if for all `x` in the domain of `T` and `y` in the
domain of `S`, we have that `⟪T x, y⟫ = ⟪x, S y⟫`. -/
def IsFormalAdjoint (T : E →ₗ.[𝕜] F) (S : F →ₗ.[𝕜] E) : Prop :=
∀ (x : T.domain) (y : S.domain), ⟪T x, y⟫ = ⟪(x : E), S y⟫
variable {T : E →ₗ.[𝕜] F} {S : F →ₗ.[𝕜] E}
@[symm]
protected theorem IsFormalAdjoint.symm (h : T.IsFormalAdjoint S) :
S.IsFormalAdjoint T := fun y _ => by
rw [← inner_conj_symm, ← inner_conj_symm (y : F), h]
variable (T)
/-- The domain of the adjoint operator.
This definition is needed to construct the adjoint operator and the preferred version to use is
`T.adjoint.domain` instead of `T.adjointDomain`. -/
def adjointDomain : Submodule 𝕜 F where
carrier := {y | Continuous ((innerₛₗ 𝕜 y).comp T.toFun)}
zero_mem' := by
rw [Set.mem_setOf_eq, LinearMap.map_zero, LinearMap.zero_comp]
exact continuous_zero
add_mem' hx hy := by rw [Set.mem_setOf_eq, LinearMap.map_add] at *; exact hx.add hy
smul_mem' a x hx := by
rw [Set.mem_setOf_eq, LinearMap.map_smulₛₗ] at *
exact hx.const_smul (conj a)
/-- The operator `fun x ↦ ⟪y, T x⟫` considered as a continuous linear operator
from `T.adjointDomain` to `𝕜`. -/
def adjointDomainMkCLM (y : T.adjointDomain) : T.domain →L[𝕜] 𝕜 :=
⟨(innerₛₗ 𝕜 (y : F)).comp T.toFun, y.prop⟩
theorem adjointDomainMkCLM_apply (y : T.adjointDomain) (x : T.domain) :
adjointDomainMkCLM T y x = ⟪(y : F), T x⟫ :=
rfl
variable {T}
variable (hT : Dense (T.domain : Set E))
/-- The unique continuous extension of the operator `adjointDomainMkCLM` to `E`. -/
def adjointDomainMkCLMExtend (y : T.adjointDomain) : E →L[𝕜] 𝕜 :=
(T.adjointDomainMkCLM y).extend (Submodule.subtypeL T.domain) hT.denseRange_val
isUniformEmbedding_subtype_val.isUniformInducing
@[simp]
theorem adjointDomainMkCLMExtend_apply (y : T.adjointDomain) (x : T.domain) :
adjointDomainMkCLMExtend hT y (x : E) = ⟪(y : F), T x⟫ :=
ContinuousLinearMap.extend_eq _ _ _ _ _
variable [CompleteSpace E]
/-- The adjoint as a linear map from its domain to `E`.
This is an auxiliary definition needed to define the adjoint operator as a `LinearPMap` without
the assumption that `T.domain` is dense. -/
def adjointAux : T.adjointDomain →ₗ[𝕜] E where
toFun y := (InnerProductSpace.toDual 𝕜 E).symm (adjointDomainMkCLMExtend hT y)
map_add' x y :=
hT.eq_of_inner_left fun _ => by
simp only [inner_add_left, Submodule.coe_add, InnerProductSpace.toDual_symm_apply,
adjointDomainMkCLMExtend_apply]
map_smul' _ _ :=
hT.eq_of_inner_left fun _ => by
simp only [inner_smul_left, Submodule.coe_smul_of_tower, RingHom.id_apply,
InnerProductSpace.toDual_symm_apply, adjointDomainMkCLMExtend_apply]
theorem adjointAux_inner (y : T.adjointDomain) (x : T.domain) :
⟪adjointAux hT y, x⟫ = ⟪(y : F), T x⟫ := by
simp [adjointAux]
theorem adjointAux_unique (y : T.adjointDomain) {x₀ : E}
(hx₀ : ∀ x : T.domain, ⟪x₀, x⟫ = ⟪(y : F), T x⟫) : adjointAux hT y = x₀ :=
hT.eq_of_inner_left fun v => (adjointAux_inner hT _ _).trans (hx₀ v).symm
variable (T)
open scoped Classical in
/-- The adjoint operator as a partially defined linear operator, denoted as `T†`. -/
def adjoint : F →ₗ.[𝕜] E where
domain := T.adjointDomain
toFun := if hT : Dense (T.domain : Set E) then adjointAux hT else 0
@[inherit_doc]
scoped postfix:1024 "†" => LinearPMap.adjoint
theorem mem_adjoint_domain_iff (y : F) : y ∈ T†.domain ↔ Continuous ((innerₛₗ 𝕜 y).comp T.toFun) :=
Iff.rfl
variable {T}
theorem mem_adjoint_domain_of_exists (y : F) (h : ∃ w : E, ∀ x : T.domain, ⟪w, x⟫ = ⟪y, T x⟫) :
y ∈ T†.domain := by
obtain ⟨w, hw⟩ := h
rw [T.mem_adjoint_domain_iff]
have : Continuous ((innerSL 𝕜 w).comp T.domain.subtypeL) := by fun_prop
convert this using 1
exact funext fun x => (hw x).symm
theorem adjoint_apply_of_not_dense (hT : ¬Dense (T.domain : Set E)) (y : T†.domain) : T† y = 0 := by
classical
change (if hT : Dense (T.domain : Set E) then adjointAux hT else 0) y = _
simp only [hT, not_false_iff, dif_neg, LinearMap.zero_apply]
theorem adjoint_apply_of_dense (y : T†.domain) : T† y = adjointAux hT y := by
classical
change (if hT : Dense (T.domain : Set E) then adjointAux hT else 0) y = _
simp only [hT, dif_pos, LinearMap.coe_mk]
include hT in
theorem adjoint_apply_eq (y : T†.domain) {x₀ : E} (hx₀ : ∀ x : T.domain, ⟪x₀, x⟫ = ⟪(y : F), T x⟫) :
T† y = x₀ :=
(adjoint_apply_of_dense hT y).symm ▸ adjointAux_unique hT _ hx₀
include hT in
/-- The fundamental property of the adjoint. -/
theorem adjoint_isFormalAdjoint : T†.IsFormalAdjoint T := fun x =>
(adjoint_apply_of_dense hT x).symm ▸ adjointAux_inner hT x
include hT in
/-- The adjoint is maximal in the sense that it contains every formal adjoint. -/
theorem IsFormalAdjoint.le_adjoint (h : T.IsFormalAdjoint S) : S ≤ T† :=
⟨-- Trivially, every `x : S.domain` is in `T.adjoint.domain`
fun x hx =>
mem_adjoint_domain_of_exists _
⟨S ⟨x, hx⟩, h.symm ⟨x, hx⟩⟩,-- Equality on `S.domain` follows from equality
-- `⟪v, S x⟫ = ⟪v, T.adjoint y⟫` for all `v : T.domain`:
fun _ _ hxy => (adjoint_apply_eq hT _ fun _ => by rw [h.symm, hxy]).symm⟩
end LinearPMap
namespace ContinuousLinearMap
variable [CompleteSpace E] [CompleteSpace F]
variable (A : E →L[𝕜] F) {p : Submodule 𝕜 E}
/-- Restricting `A` to a dense submodule and taking the `LinearPMap.adjoint` is the same
as taking the `ContinuousLinearMap.adjoint` interpreted as a `LinearPMap`. -/
| Mathlib/Analysis/InnerProductSpace/LinearPMap.lean | 201 | 207 | theorem toPMap_adjoint_eq_adjoint_toPMap_of_dense (hp : Dense (p : Set E)) :
(A.toPMap p).adjoint = A.adjoint.toPMap ⊤ := by | ext x y hxy
· simp only [LinearMap.toPMap_domain, Submodule.mem_top, iff_true,
LinearPMap.mem_adjoint_domain_iff, LinearMap.coe_comp, innerₛₗ_apply_coe]
exact ((innerSL 𝕜 x).comp <| A.comp <| Submodule.subtypeL _).cont
refine LinearPMap.adjoint_apply_eq hp _ fun v => ?_ |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Yury Kudryashov
-/
import Mathlib.Topology.Order.LeftRight
import Mathlib.Topology.Separation.Hausdorff
/-!
# Order-closed topologies
In this file we introduce 3 typeclass mixins that relate topology and order structures:
- `ClosedIicTopology` says that all the intervals $(-∞, a]$ (formally, `Set.Iic a`)
are closed sets;
- `ClosedIciTopology` says that all the intervals $[a, +∞)$ (formally, `Set.Ici a`)
are closed sets;
- `OrderClosedTopology` says that the set of points `(x, y)` such that `x ≤ y`
is closed in the product topology.
The last predicate implies the first two.
We prove many basic properties of such topologies.
## Main statements
This file contains the proofs of the following facts.
For exact requirements
(`OrderClosedTopology` vs `ClosedIciTopology` vs `ClosedIicTopology,
`Preorder` vs `PartialOrder` vs `LinearOrder` etc)
see their statements.
### Open / closed sets
* `isOpen_lt` : if `f` and `g` are continuous functions, then `{x | f x < g x}` is open;
* `isOpen_Iio`, `isOpen_Ioi`, `isOpen_Ioo` : open intervals are open;
* `isClosed_le` : if `f` and `g` are continuous functions, then `{x | f x ≤ g x}` is closed;
* `isClosed_Iic`, `isClosed_Ici`, `isClosed_Icc` : closed intervals are closed;
* `frontier_le_subset_eq`, `frontier_lt_subset_eq` : frontiers of both `{x | f x ≤ g x}`
and `{x | f x < g x}` are included by `{x | f x = g x}`;
### Convergence and inequalities
* `le_of_tendsto_of_tendsto` : if `f` converges to `a`, `g` converges to `b`, and eventually
`f x ≤ g x`, then `a ≤ b`
* `le_of_tendsto`, `ge_of_tendsto` : if `f` converges to `a` and eventually `f x ≤ b`
(resp., `b ≤ f x`), then `a ≤ b` (resp., `b ≤ a`); we also provide primed versions
that assume the inequalities to hold for all `x`.
### Min, max, `sSup` and `sInf`
* `Continuous.min`, `Continuous.max`: pointwise `min`/`max` of two continuous functions is
continuous.
* `Tendsto.min`, `Tendsto.max` : if `f` tends to `a` and `g` tends to `b`, then their pointwise
`min`/`max` tend to `min a b` and `max a b`, respectively.
-/
open Set Filter
open OrderDual (toDual)
open scoped Topology
universe u v w
variable {α : Type u} {β : Type v} {γ : Type w}
/-- If `α` is a topological space and a preorder, `ClosedIicTopology α` means that `Iic a` is
closed for all `a : α`. -/
class ClosedIicTopology (α : Type*) [TopologicalSpace α] [Preorder α] : Prop where
/-- For any `a`, the set `(-∞, a]` is closed. -/
isClosed_Iic (a : α) : IsClosed (Iic a)
/-- If `α` is a topological space and a preorder, `ClosedIciTopology α` means that `Ici a` is
closed for all `a : α`. -/
class ClosedIciTopology (α : Type*) [TopologicalSpace α] [Preorder α] : Prop where
/-- For any `a`, the set `[a, +∞)` is closed. -/
isClosed_Ici (a : α) : IsClosed (Ici a)
/-- A topology on a set which is both a topological space and a preorder is _order-closed_ if the
set of points `(x, y)` with `x ≤ y` is closed in the product space. We introduce this as a mixin.
This property is satisfied for the order topology on a linear order, but it can be satisfied more
generally, and suffices to derive many interesting properties relating order and topology. -/
class OrderClosedTopology (α : Type*) [TopologicalSpace α] [Preorder α] : Prop where
/-- The set `{ (x, y) | x ≤ y }` is a closed set. -/
isClosed_le' : IsClosed { p : α × α | p.1 ≤ p.2 }
instance [TopologicalSpace α] [h : FirstCountableTopology α] : FirstCountableTopology αᵒᵈ := h
instance [TopologicalSpace α] [h : SecondCountableTopology α] : SecondCountableTopology αᵒᵈ := h
theorem Dense.orderDual [TopologicalSpace α] {s : Set α} (hs : Dense s) :
Dense (OrderDual.ofDual ⁻¹' s) :=
hs
section General
variable [TopologicalSpace α] [Preorder α] {s : Set α}
protected lemma BddAbove.of_closure : BddAbove (closure s) → BddAbove s :=
BddAbove.mono subset_closure
protected lemma BddBelow.of_closure : BddBelow (closure s) → BddBelow s :=
BddBelow.mono subset_closure
end General
section ClosedIicTopology
section Preorder
variable [TopologicalSpace α] [Preorder α] [ClosedIicTopology α] {f : β → α} {a b : α} {s : Set α}
theorem isClosed_Iic : IsClosed (Iic a) :=
ClosedIicTopology.isClosed_Iic a
instance : ClosedIciTopology αᵒᵈ where
isClosed_Ici _ := isClosed_Iic (α := α)
@[simp]
theorem closure_Iic (a : α) : closure (Iic a) = Iic a :=
isClosed_Iic.closure_eq
theorem le_of_tendsto_of_frequently {x : Filter β} (lim : Tendsto f x (𝓝 a))
(h : ∃ᶠ c in x, f c ≤ b) : a ≤ b :=
isClosed_Iic.mem_of_frequently_of_tendsto h lim
theorem le_of_tendsto {x : Filter β} [NeBot x] (lim : Tendsto f x (𝓝 a))
(h : ∀ᶠ c in x, f c ≤ b) : a ≤ b :=
isClosed_Iic.mem_of_tendsto lim h
theorem le_of_tendsto' {x : Filter β} [NeBot x] (lim : Tendsto f x (𝓝 a))
(h : ∀ c, f c ≤ b) : a ≤ b :=
le_of_tendsto lim (Eventually.of_forall h)
@[simp] lemma upperBounds_closure (s : Set α) : upperBounds (closure s : Set α) = upperBounds s :=
ext fun a ↦ by simp_rw [mem_upperBounds_iff_subset_Iic, isClosed_Iic.closure_subset_iff]
@[simp] lemma bddAbove_closure : BddAbove (closure s) ↔ BddAbove s := by
simp_rw [BddAbove, upperBounds_closure]
protected alias ⟨_, BddAbove.closure⟩ := bddAbove_closure
@[simp]
theorem disjoint_nhds_atBot_iff : Disjoint (𝓝 a) atBot ↔ ¬IsBot a := by
constructor
· intro hd hbot
rw [hbot.atBot_eq, disjoint_principal_right] at hd
exact mem_of_mem_nhds hd le_rfl
· simp only [IsBot, not_forall]
rintro ⟨b, hb⟩
refine disjoint_of_disjoint_of_mem disjoint_compl_left ?_ (Iic_mem_atBot b)
exact isClosed_Iic.isOpen_compl.mem_nhds hb
theorem IsLUB.range_of_tendsto {F : Filter β} [F.NeBot] (hle : ∀ i, f i ≤ a)
(hlim : Tendsto f F (𝓝 a)) : IsLUB (range f) a :=
⟨forall_mem_range.mpr hle, fun _c hc ↦ le_of_tendsto' hlim fun i ↦ hc <| mem_range_self i⟩
end Preorder
section NoBotOrder
variable [Preorder α] [NoBotOrder α] [TopologicalSpace α] [ClosedIicTopology α] {a : α}
{l : Filter β} [NeBot l] {f : β → α}
theorem disjoint_nhds_atBot (a : α) : Disjoint (𝓝 a) atBot := by simp
@[simp]
theorem inf_nhds_atBot (a : α) : 𝓝 a ⊓ atBot = ⊥ := (disjoint_nhds_atBot a).eq_bot
theorem not_tendsto_nhds_of_tendsto_atBot (hf : Tendsto f l atBot) (a : α) : ¬Tendsto f l (𝓝 a) :=
hf.not_tendsto (disjoint_nhds_atBot a).symm
theorem not_tendsto_atBot_of_tendsto_nhds (hf : Tendsto f l (𝓝 a)) : ¬Tendsto f l atBot :=
hf.not_tendsto (disjoint_nhds_atBot a)
end NoBotOrder
theorem iSup_eq_of_forall_le_of_tendsto {ι : Type*} {F : Filter ι} [Filter.NeBot F]
[ConditionallyCompleteLattice α] [TopologicalSpace α] [ClosedIicTopology α]
{a : α} {f : ι → α} (hle : ∀ i, f i ≤ a) (hlim : Filter.Tendsto f F (𝓝 a)) :
⨆ i, f i = a :=
have := F.nonempty_of_neBot
(IsLUB.range_of_tendsto hle hlim).ciSup_eq
theorem iUnion_Iic_eq_Iio_of_lt_of_tendsto {ι : Type*} {F : Filter ι} [F.NeBot]
[ConditionallyCompleteLinearOrder α] [TopologicalSpace α] [ClosedIicTopology α]
{a : α} {f : ι → α} (hlt : ∀ i, f i < a) (hlim : Tendsto f F (𝓝 a)) :
⋃ i : ι, Iic (f i) = Iio a := by
have obs : a ∉ range f := by
rw [mem_range]
rintro ⟨i, rfl⟩
exact (hlt i).false
rw [← biUnion_range, (IsLUB.range_of_tendsto (le_of_lt <| hlt ·) hlim).biUnion_Iic_eq_Iio obs]
section LinearOrder
variable [TopologicalSpace α] [LinearOrder α] [ClosedIicTopology α] [TopologicalSpace β]
{a b c : α} {f : α → β}
theorem isOpen_Ioi : IsOpen (Ioi a) := by
rw [← compl_Iic]
exact isClosed_Iic.isOpen_compl
@[simp]
theorem interior_Ioi : interior (Ioi a) = Ioi a :=
isOpen_Ioi.interior_eq
theorem Ioi_mem_nhds (h : a < b) : Ioi a ∈ 𝓝 b := IsOpen.mem_nhds isOpen_Ioi h
theorem eventually_gt_nhds (hab : b < a) : ∀ᶠ x in 𝓝 a, b < x := Ioi_mem_nhds hab
theorem Ici_mem_nhds (h : a < b) : Ici a ∈ 𝓝 b :=
mem_of_superset (Ioi_mem_nhds h) Ioi_subset_Ici_self
theorem eventually_ge_nhds (hab : b < a) : ∀ᶠ x in 𝓝 a, b ≤ x := Ici_mem_nhds hab
theorem Filter.Tendsto.eventually_const_lt {l : Filter γ} {f : γ → α} {u v : α} (hv : u < v)
(h : Filter.Tendsto f l (𝓝 v)) : ∀ᶠ a in l, u < f a :=
h.eventually <| eventually_gt_nhds hv
@[deprecated (since := "2024-11-17")]
alias eventually_gt_of_tendsto_gt := Filter.Tendsto.eventually_const_lt
theorem Filter.Tendsto.eventually_const_le {l : Filter γ} {f : γ → α} {u v : α} (hv : u < v)
(h : Tendsto f l (𝓝 v)) : ∀ᶠ a in l, u ≤ f a :=
h.eventually <| eventually_ge_nhds hv
@[deprecated (since := "2024-11-17")]
alias eventually_ge_of_tendsto_gt := Filter.Tendsto.eventually_const_le
protected theorem Dense.exists_gt [NoMaxOrder α] {s : Set α} (hs : Dense s) (x : α) :
∃ y ∈ s, x < y :=
hs.exists_mem_open isOpen_Ioi (exists_gt x)
protected theorem Dense.exists_ge [NoMaxOrder α] {s : Set α} (hs : Dense s) (x : α) :
∃ y ∈ s, x ≤ y :=
(hs.exists_gt x).imp fun _ h ↦ ⟨h.1, h.2.le⟩
theorem Dense.exists_ge' {s : Set α} (hs : Dense s) (htop : ∀ x, IsTop x → x ∈ s) (x : α) :
∃ y ∈ s, x ≤ y := by
by_cases hx : IsTop x
· exact ⟨x, htop x hx, le_rfl⟩
· simp only [IsTop, not_forall, not_le] at hx
rcases hs.exists_mem_open isOpen_Ioi hx with ⟨y, hys, hy : x < y⟩
exact ⟨y, hys, hy.le⟩
/-!
### Left neighborhoods on a `ClosedIicTopology`
Limits to the left of real functions are defined in terms of neighborhoods to the left,
either open or closed, i.e., members of `𝓝[<] a` and `𝓝[≤] a`.
Here we prove that all left-neighborhoods of a point are equal,
and we prove other useful characterizations which require the stronger hypothesis `OrderTopology α`
in another file.
-/
/-!
#### Point excluded
-/
theorem Ioo_mem_nhdsLT (H : a < b) : Ioo a b ∈ 𝓝[<] b := by
simpa only [← Iio_inter_Ioi] using inter_mem_nhdsWithin _ (Ioi_mem_nhds H)
@[deprecated (since := "2024-12-21")] alias Ioo_mem_nhdsWithin_Iio' := Ioo_mem_nhdsLT
theorem Ioo_mem_nhdsLT_of_mem (H : b ∈ Ioc a c) : Ioo a c ∈ 𝓝[<] b :=
mem_of_superset (Ioo_mem_nhdsLT H.1) <| Ioo_subset_Ioo_right H.2
@[deprecated (since := "2024-12-21")] alias Ioo_mem_nhdsWithin_Iio := Ioo_mem_nhdsLT_of_mem
protected theorem CovBy.nhdsLT (h : a ⋖ b) : 𝓝[<] b = ⊥ :=
empty_mem_iff_bot.mp <| h.Ioo_eq ▸ Ioo_mem_nhdsLT h.1
@[deprecated (since := "2024-12-21")] protected alias CovBy.nhdsWithin_Iio := CovBy.nhdsLT
protected theorem PredOrder.nhdsLT [PredOrder α] : 𝓝[<] a = ⊥ := by
if h : IsMin a then simp [h.Iio_eq]
else exact (Order.pred_covBy_of_not_isMin h).nhdsLT
@[deprecated (since := "2024-12-21")] protected alias PredOrder.nhdsWithin_Iio := PredOrder.nhdsLT
theorem PredOrder.nhdsGT_eq_nhdsNE [PredOrder α] (a : α) : 𝓝[>] a = 𝓝[≠] a := by
rw [← nhdsLT_sup_nhdsGT, PredOrder.nhdsLT, bot_sup_eq]
theorem PredOrder.nhdsGE_eq_nhds [PredOrder α] (a : α) : 𝓝[≥] a = 𝓝 a := by
rw [← nhdsLT_sup_nhdsGE, PredOrder.nhdsLT, bot_sup_eq]
theorem Ico_mem_nhdsLT_of_mem (H : b ∈ Ioc a c) : Ico a c ∈ 𝓝[<] b :=
mem_of_superset (Ioo_mem_nhdsLT_of_mem H) Ioo_subset_Ico_self
@[deprecated (since := "2024-12-21")] alias Ico_mem_nhdsWithin_Iio := Ico_mem_nhdsLT_of_mem
theorem Ico_mem_nhdsLT (H : a < b) : Ico a b ∈ 𝓝[<] b := Ico_mem_nhdsLT_of_mem ⟨H, le_rfl⟩
@[deprecated (since := "2024-12-21")] alias Ico_mem_nhdsWithin_Iio' := Ico_mem_nhdsLT
theorem Ioc_mem_nhdsLT_of_mem (H : b ∈ Ioc a c) : Ioc a c ∈ 𝓝[<] b :=
mem_of_superset (Ioo_mem_nhdsLT_of_mem H) Ioo_subset_Ioc_self
@[deprecated (since := "2024-12-21")] alias Ioc_mem_nhdsWithin_Iio := Ioc_mem_nhdsLT_of_mem
theorem Ioc_mem_nhdsLT (H : a < b) : Ioc a b ∈ 𝓝[<] b := Ioc_mem_nhdsLT_of_mem ⟨H, le_rfl⟩
@[deprecated (since := "2024-12-21")] alias Ioc_mem_nhdsWithin_Iio' := Ioc_mem_nhdsLT
theorem Icc_mem_nhdsLT_of_mem (H : b ∈ Ioc a c) : Icc a c ∈ 𝓝[<] b :=
mem_of_superset (Ioo_mem_nhdsLT_of_mem H) Ioo_subset_Icc_self
@[deprecated (since := "2024-12-21")] alias Icc_mem_nhdsWithin_Iio := Icc_mem_nhdsLT_of_mem
theorem Icc_mem_nhdsLT (H : a < b) : Icc a b ∈ 𝓝[<] b := Icc_mem_nhdsLT_of_mem ⟨H, le_rfl⟩
@[deprecated (since := "2024-12-21")] alias Icc_mem_nhdsWithin_Iio' := Icc_mem_nhdsLT
@[simp]
theorem nhdsWithin_Ico_eq_nhdsLT (h : a < b) : 𝓝[Ico a b] b = 𝓝[<] b :=
nhdsWithin_inter_of_mem <| nhdsWithin_le_nhds <| Ici_mem_nhds h
@[deprecated (since := "2024-12-21")]
alias nhdsWithin_Ico_eq_nhdsWithin_Iio := nhdsWithin_Ico_eq_nhdsLT
@[simp]
theorem nhdsWithin_Ioo_eq_nhdsLT (h : a < b) : 𝓝[Ioo a b] b = 𝓝[<] b :=
nhdsWithin_inter_of_mem <| nhdsWithin_le_nhds <| Ioi_mem_nhds h
@[deprecated (since := "2024-12-21")]
alias nhdsWithin_Ioo_eq_nhdsWithin_Iio := nhdsWithin_Ioo_eq_nhdsLT
@[simp]
theorem continuousWithinAt_Ico_iff_Iio (h : a < b) :
ContinuousWithinAt f (Ico a b) b ↔ ContinuousWithinAt f (Iio b) b := by
simp only [ContinuousWithinAt, nhdsWithin_Ico_eq_nhdsLT h]
@[simp]
theorem continuousWithinAt_Ioo_iff_Iio (h : a < b) :
ContinuousWithinAt f (Ioo a b) b ↔ ContinuousWithinAt f (Iio b) b := by
simp only [ContinuousWithinAt, nhdsWithin_Ioo_eq_nhdsLT h]
/-!
#### Point included
-/
protected theorem CovBy.nhdsLE (H : a ⋖ b) : 𝓝[≤] b = pure b := by
rw [← Iio_insert, nhdsWithin_insert, H.nhdsLT, sup_bot_eq]
@[deprecated (since := "2024-12-21")]
protected alias CovBy.nhdsWithin_Iic := CovBy.nhdsLE
protected theorem PredOrder.nhdsLE [PredOrder α] : 𝓝[≤] b = pure b := by
rw [← Iio_insert, nhdsWithin_insert, PredOrder.nhdsLT, sup_bot_eq]
@[deprecated (since := "2024-12-21")]
protected alias PredOrder.nhdsWithin_Iic := PredOrder.nhdsLE
theorem Ioc_mem_nhdsLE (H : a < b) : Ioc a b ∈ 𝓝[≤] b :=
inter_mem (nhdsWithin_le_nhds <| Ioi_mem_nhds H) self_mem_nhdsWithin
@[deprecated (since := "2024-12-21")] alias Ioc_mem_nhdsWithin_Iic' := Ioc_mem_nhdsLE
theorem Ioo_mem_nhdsLE_of_mem (H : b ∈ Ioo a c) : Ioo a c ∈ 𝓝[≤] b :=
mem_of_superset (Ioc_mem_nhdsLE H.1) <| Ioc_subset_Ioo_right H.2
@[deprecated (since := "2024-12-21")] alias Ioo_mem_nhdsWithin_Iic := Ioo_mem_nhdsLE_of_mem
theorem Ico_mem_nhdsLE_of_mem (H : b ∈ Ioo a c) : Ico a c ∈ 𝓝[≤] b :=
mem_of_superset (Ioo_mem_nhdsLE_of_mem H) Ioo_subset_Ico_self
@[deprecated (since := "2024-12-22")]
alias Ico_mem_nhdsWithin_Iic := Ico_mem_nhdsLE_of_mem
theorem Ioc_mem_nhdsLE_of_mem (H : b ∈ Ioc a c) : Ioc a c ∈ 𝓝[≤] b :=
mem_of_superset (Ioc_mem_nhdsLE H.1) <| Ioc_subset_Ioc_right H.2
@[deprecated (since := "2024-12-22")]
alias Ioc_mem_nhdsWithin_Iic := Ioc_mem_nhdsLE_of_mem
theorem Icc_mem_nhdsLE_of_mem (H : b ∈ Ioc a c) : Icc a c ∈ 𝓝[≤] b :=
mem_of_superset (Ioc_mem_nhdsLE_of_mem H) Ioc_subset_Icc_self
@[deprecated (since := "2024-12-22")]
alias Icc_mem_nhdsWithin_Iic := Icc_mem_nhdsLE_of_mem
theorem Icc_mem_nhdsLE (H : a < b) : Icc a b ∈ 𝓝[≤] b := Icc_mem_nhdsLE_of_mem ⟨H, le_rfl⟩
@[deprecated (since := "2024-12-22")]
alias Icc_mem_nhdsWithin_Iic' := Icc_mem_nhdsLE
@[simp]
theorem nhdsWithin_Icc_eq_nhdsLE (h : a < b) : 𝓝[Icc a b] b = 𝓝[≤] b :=
nhdsWithin_inter_of_mem <| nhdsWithin_le_nhds <| Ici_mem_nhds h
@[deprecated (since := "2024-12-22")]
alias nhdsWithin_Icc_eq_nhdsWithin_Iic := nhdsWithin_Icc_eq_nhdsLE
@[simp]
theorem nhdsWithin_Ioc_eq_nhdsLE (h : a < b) : 𝓝[Ioc a b] b = 𝓝[≤] b :=
nhdsWithin_inter_of_mem <| nhdsWithin_le_nhds <| Ioi_mem_nhds h
@[deprecated (since := "2024-12-22")]
alias nhdsWithin_Ioc_eq_nhdsWithin_Iic := nhdsWithin_Ioc_eq_nhdsLE
@[simp]
theorem continuousWithinAt_Icc_iff_Iic (h : a < b) :
ContinuousWithinAt f (Icc a b) b ↔ ContinuousWithinAt f (Iic b) b := by
simp only [ContinuousWithinAt, nhdsWithin_Icc_eq_nhdsLE h]
@[simp]
theorem continuousWithinAt_Ioc_iff_Iic (h : a < b) :
ContinuousWithinAt f (Ioc a b) b ↔ ContinuousWithinAt f (Iic b) b := by
simp only [ContinuousWithinAt, nhdsWithin_Ioc_eq_nhdsLE h]
end LinearOrder
end ClosedIicTopology
section ClosedIciTopology
section Preorder
variable [TopologicalSpace α] [Preorder α] [ClosedIciTopology α] {f : β → α} {a b : α} {s : Set α}
theorem isClosed_Ici {a : α} : IsClosed (Ici a) :=
ClosedIciTopology.isClosed_Ici a
instance : ClosedIicTopology αᵒᵈ where
isClosed_Iic _ := isClosed_Ici (α := α)
@[simp]
theorem closure_Ici (a : α) : closure (Ici a) = Ici a :=
isClosed_Ici.closure_eq
lemma ge_of_tendsto_of_frequently {x : Filter β} (lim : Tendsto f x (𝓝 a))
(h : ∃ᶠ c in x, b ≤ f c) : b ≤ a :=
isClosed_Ici.mem_of_frequently_of_tendsto h lim
theorem ge_of_tendsto {x : Filter β} [NeBot x] (lim : Tendsto f x (𝓝 a))
(h : ∀ᶠ c in x, b ≤ f c) : b ≤ a :=
isClosed_Ici.mem_of_tendsto lim h
theorem ge_of_tendsto' {x : Filter β} [NeBot x] (lim : Tendsto f x (𝓝 a))
(h : ∀ c, b ≤ f c) : b ≤ a :=
ge_of_tendsto lim (Eventually.of_forall h)
@[simp] lemma lowerBounds_closure (s : Set α) : lowerBounds (closure s : Set α) = lowerBounds s :=
ext fun a ↦ by simp_rw [mem_lowerBounds_iff_subset_Ici, isClosed_Ici.closure_subset_iff]
@[simp] lemma bddBelow_closure : BddBelow (closure s) ↔ BddBelow s := by
simp_rw [BddBelow, lowerBounds_closure]
protected alias ⟨_, BddBelow.closure⟩ := bddBelow_closure
@[simp]
theorem disjoint_nhds_atTop_iff : Disjoint (𝓝 a) atTop ↔ ¬IsTop a :=
disjoint_nhds_atBot_iff (α := αᵒᵈ)
theorem IsGLB.range_of_tendsto {F : Filter β} [F.NeBot] (hle : ∀ i, a ≤ f i)
(hlim : Tendsto f F (𝓝 a)) : IsGLB (range f) a :=
IsLUB.range_of_tendsto (α := αᵒᵈ) hle hlim
end Preorder
section NoTopOrder
variable [Preorder α] [NoTopOrder α] [TopologicalSpace α] [ClosedIciTopology α] {a : α}
{l : Filter β} [NeBot l] {f : β → α}
theorem disjoint_nhds_atTop (a : α) : Disjoint (𝓝 a) atTop := disjoint_nhds_atBot (toDual a)
@[simp]
theorem inf_nhds_atTop (a : α) : 𝓝 a ⊓ atTop = ⊥ := (disjoint_nhds_atTop a).eq_bot
theorem not_tendsto_nhds_of_tendsto_atTop (hf : Tendsto f l atTop) (a : α) : ¬Tendsto f l (𝓝 a) :=
hf.not_tendsto (disjoint_nhds_atTop a).symm
theorem not_tendsto_atTop_of_tendsto_nhds (hf : Tendsto f l (𝓝 a)) : ¬Tendsto f l atTop :=
hf.not_tendsto (disjoint_nhds_atTop a)
end NoTopOrder
theorem iInf_eq_of_forall_le_of_tendsto {ι : Type*} {F : Filter ι} [F.NeBot]
[ConditionallyCompleteLattice α] [TopologicalSpace α] [ClosedIciTopology α]
{a : α} {f : ι → α} (hle : ∀ i, a ≤ f i) (hlim : Tendsto f F (𝓝 a)) :
⨅ i, f i = a :=
iSup_eq_of_forall_le_of_tendsto (α := αᵒᵈ) hle hlim
theorem iUnion_Ici_eq_Ioi_of_lt_of_tendsto {ι : Type*} {F : Filter ι} [F.NeBot]
[ConditionallyCompleteLinearOrder α] [TopologicalSpace α] [ClosedIciTopology α]
{a : α} {f : ι → α} (hlt : ∀ i, a < f i) (hlim : Tendsto f F (𝓝 a)) :
⋃ i : ι, Ici (f i) = Ioi a :=
iUnion_Iic_eq_Iio_of_lt_of_tendsto (α := αᵒᵈ) hlt hlim
section LinearOrder
variable [TopologicalSpace α] [LinearOrder α] [ClosedIciTopology α] [TopologicalSpace β]
{a b c : α} {f : α → β}
theorem isOpen_Iio : IsOpen (Iio a) := isOpen_Ioi (α := αᵒᵈ)
@[simp] theorem interior_Iio : interior (Iio a) = Iio a := isOpen_Iio.interior_eq
theorem Iio_mem_nhds (h : a < b) : Iio b ∈ 𝓝 a := isOpen_Iio.mem_nhds h
theorem eventually_lt_nhds (hab : a < b) : ∀ᶠ x in 𝓝 a, x < b := Iio_mem_nhds hab
theorem Iic_mem_nhds (h : a < b) : Iic b ∈ 𝓝 a :=
mem_of_superset (Iio_mem_nhds h) Iio_subset_Iic_self
theorem eventually_le_nhds (hab : a < b) : ∀ᶠ x in 𝓝 a, x ≤ b := Iic_mem_nhds hab
theorem Filter.Tendsto.eventually_lt_const {l : Filter γ} {f : γ → α} {u v : α} (hv : v < u)
(h : Filter.Tendsto f l (𝓝 v)) : ∀ᶠ a in l, f a < u :=
h.eventually <| eventually_lt_nhds hv
@[deprecated (since := "2024-11-17")]
alias eventually_lt_of_tendsto_lt := Filter.Tendsto.eventually_lt_const
theorem Filter.Tendsto.eventually_le_const {l : Filter γ} {f : γ → α} {u v : α} (hv : v < u)
(h : Tendsto f l (𝓝 v)) : ∀ᶠ a in l, f a ≤ u :=
h.eventually <| eventually_le_nhds hv
@[deprecated (since := "2024-11-17")]
alias eventually_le_of_tendsto_lt := Filter.Tendsto.eventually_le_const
protected theorem Dense.exists_lt [NoMinOrder α] {s : Set α} (hs : Dense s) (x : α) :
∃ y ∈ s, y < x :=
hs.orderDual.exists_gt x
protected theorem Dense.exists_le [NoMinOrder α] {s : Set α} (hs : Dense s) (x : α) :
∃ y ∈ s, y ≤ x :=
hs.orderDual.exists_ge x
theorem Dense.exists_le' {s : Set α} (hs : Dense s) (hbot : ∀ x, IsBot x → x ∈ s) (x : α) :
∃ y ∈ s, y ≤ x :=
hs.orderDual.exists_ge' hbot x
/-!
### Right neighborhoods on a `ClosedIciTopology`
Limits to the right of real functions are defined in terms of neighborhoods to the right,
either open or closed, i.e., members of `𝓝[>] a` and `𝓝[≥] a`.
Here we prove that all right-neighborhoods of a point are equal,
and we prove other useful characterizations which require the stronger hypothesis `OrderTopology α`
in another file.
-/
/-!
#### Point excluded
-/
theorem Ioo_mem_nhdsGT_of_mem (H : b ∈ Ico a c) : Ioo a c ∈ 𝓝[>] b :=
mem_nhdsWithin.2
⟨Iio c, isOpen_Iio, H.2, by rw [inter_comm, Ioi_inter_Iio]; exact Ioo_subset_Ioo_left H.1⟩
@[deprecated (since := "2024-12-22")] alias Ioo_mem_nhdsWithin_Ioi := Ioo_mem_nhdsGT_of_mem
theorem Ioo_mem_nhdsGT (H : a < b) : Ioo a b ∈ 𝓝[>] a := Ioo_mem_nhdsGT_of_mem ⟨le_rfl, H⟩
@[deprecated (since := "2024-12-22")] alias Ioo_mem_nhdsWithin_Ioi' := Ioo_mem_nhdsGT
protected theorem CovBy.nhdsGT (h : a ⋖ b) : 𝓝[>] a = ⊥ := h.toDual.nhdsLT
@[deprecated (since := "2024-12-22")] alias CovBy.nhdsWithin_Ioi := CovBy.nhdsGT
protected theorem SuccOrder.nhdsGT [SuccOrder α] : 𝓝[>] a = ⊥ := PredOrder.nhdsLT (α := αᵒᵈ)
@[deprecated (since := "2024-12-22")] alias SuccOrder.nhdsWithin_Ioi := SuccOrder.nhdsGT
theorem SuccOrder.nhdsLT_eq_nhdsNE [SuccOrder α] (a : α) : 𝓝[<] a = 𝓝[≠] a :=
PredOrder.nhdsGT_eq_nhdsNE (α := αᵒᵈ) a
theorem SuccOrder.nhdsLE_eq_nhds [SuccOrder α] (a : α) : 𝓝[≤] a = 𝓝 a :=
PredOrder.nhdsGE_eq_nhds (α := αᵒᵈ) a
theorem Ioc_mem_nhdsGT_of_mem (H : b ∈ Ico a c) : Ioc a c ∈ 𝓝[>] b :=
mem_of_superset (Ioo_mem_nhdsGT_of_mem H) Ioo_subset_Ioc_self
@[deprecated (since := "2024-12-22")]
alias Ioc_mem_nhdsWithin_Ioi := Ioc_mem_nhdsGT_of_mem
theorem Ioc_mem_nhdsGT (H : a < b) : Ioc a b ∈ 𝓝[>] a := Ioc_mem_nhdsGT_of_mem ⟨le_rfl, H⟩
@[deprecated (since := "2024-12-22")] alias Ioc_mem_nhdsWithin_Ioi' := Ioc_mem_nhdsGT
theorem Ico_mem_nhdsGT_of_mem (H : b ∈ Ico a c) : Ico a c ∈ 𝓝[>] b :=
mem_of_superset (Ioo_mem_nhdsGT_of_mem H) Ioo_subset_Ico_self
@[deprecated (since := "2024-12-22")] alias Ico_mem_nhdsWithin_Ioi := Ico_mem_nhdsGT_of_mem
theorem Ico_mem_nhdsGT (H : a < b) : Ico a b ∈ 𝓝[>] a := Ico_mem_nhdsGT_of_mem ⟨le_rfl, H⟩
@[deprecated (since := "2024-12-22")] alias Ico_mem_nhdsWithin_Ioi' := Ico_mem_nhdsGT
theorem Icc_mem_nhdsGT_of_mem (H : b ∈ Ico a c) : Icc a c ∈ 𝓝[>] b :=
mem_of_superset (Ioo_mem_nhdsGT_of_mem H) Ioo_subset_Icc_self
@[deprecated (since := "2024-12-22")] alias Icc_mem_nhdsWithin_Ioi := Icc_mem_nhdsGT_of_mem
theorem Icc_mem_nhdsGT (H : a < b) : Icc a b ∈ 𝓝[>] a := Icc_mem_nhdsGT_of_mem ⟨le_rfl, H⟩
@[deprecated (since := "2024-12-22")] alias Icc_mem_nhdsWithin_Ioi' := Icc_mem_nhdsGT
@[simp]
theorem nhdsWithin_Ioc_eq_nhdsGT (h : a < b) : 𝓝[Ioc a b] a = 𝓝[>] a :=
nhdsWithin_inter_of_mem' <| nhdsWithin_le_nhds <| Iic_mem_nhds h
@[deprecated (since := "2024-12-22")]
alias nhdsWithin_Ioc_eq_nhdsWithin_Ioi := nhdsWithin_Ioc_eq_nhdsGT
@[simp]
theorem nhdsWithin_Ioo_eq_nhdsGT (h : a < b) : 𝓝[Ioo a b] a = 𝓝[>] a :=
nhdsWithin_inter_of_mem' <| nhdsWithin_le_nhds <| Iio_mem_nhds h
@[deprecated (since := "2024-12-22")]
alias nhdsWithin_Ioo_eq_nhdsWithin_Ioi := nhdsWithin_Ioo_eq_nhdsGT
@[simp]
theorem continuousWithinAt_Ioc_iff_Ioi (h : a < b) :
ContinuousWithinAt f (Ioc a b) a ↔ ContinuousWithinAt f (Ioi a) a := by
simp only [ContinuousWithinAt, nhdsWithin_Ioc_eq_nhdsGT h]
@[simp]
theorem continuousWithinAt_Ioo_iff_Ioi (h : a < b) :
ContinuousWithinAt f (Ioo a b) a ↔ ContinuousWithinAt f (Ioi a) a := by
simp only [ContinuousWithinAt, nhdsWithin_Ioo_eq_nhdsGT h]
/-!
### Point included
-/
protected theorem CovBy.nhdsGE (H : a ⋖ b) : 𝓝[≥] a = pure a := H.toDual.nhdsLE
@[deprecated (since := "2024-12-22")] alias CovBy.nhdsWithin_Ici := CovBy.nhdsGE
protected theorem SuccOrder.nhdsGE [SuccOrder α] : 𝓝[≥] a = pure a :=
PredOrder.nhdsLE (α := αᵒᵈ)
@[deprecated (since := "2024-12-22")]
alias SuccOrder.nhdsWithin_Ici := SuccOrder.nhdsGE
theorem Ico_mem_nhdsGE (H : a < b) : Ico a b ∈ 𝓝[≥] a :=
inter_mem_nhdsWithin _ <| Iio_mem_nhds H
@[deprecated (since := "2024-12-22")] alias Ico_mem_nhdsWithin_Ici' := Ico_mem_nhdsGE
theorem Ico_mem_nhdsGE_of_mem (H : b ∈ Ico a c) : Ico a c ∈ 𝓝[≥] b :=
mem_of_superset (Ico_mem_nhdsGE H.2) <| Ico_subset_Ico_left H.1
@[deprecated (since := "2024-12-22")]
alias Ico_mem_nhdsWithin_Ici := Ico_mem_nhdsGE_of_mem
theorem Ioo_mem_nhdsGE_of_mem (H : b ∈ Ioo a c) : Ioo a c ∈ 𝓝[≥] b :=
mem_of_superset (Ico_mem_nhdsGE H.2) <| Ico_subset_Ioo_left H.1
@[deprecated (since := "2024-12-22")]
alias Ioo_mem_nhdsWithin_Ici := Ioo_mem_nhdsGE_of_mem
theorem Ioc_mem_nhdsGE_of_mem (H : b ∈ Ioo a c) : Ioc a c ∈ 𝓝[≥] b :=
mem_of_superset (Ioo_mem_nhdsGE_of_mem H) Ioo_subset_Ioc_self
@[deprecated (since := "2024-12-22")] alias Ioc_mem_nhdsWithin_Ici := Ioc_mem_nhdsGE_of_mem
theorem Icc_mem_nhdsGE_of_mem (H : b ∈ Ico a c) : Icc a c ∈ 𝓝[≥] b :=
mem_of_superset (Ico_mem_nhdsGE_of_mem H) Ico_subset_Icc_self
@[deprecated (since := "2024-12-22")]
alias Icc_mem_nhdsWithin_Ici := Icc_mem_nhdsGE_of_mem
theorem Icc_mem_nhdsGE (H : a < b) : Icc a b ∈ 𝓝[≥] a := Icc_mem_nhdsGE_of_mem ⟨le_rfl, H⟩
@[deprecated (since := "2024-12-22")] alias Icc_mem_nhdsWithin_Ici' := Icc_mem_nhdsGE
@[simp]
theorem nhdsWithin_Icc_eq_nhdsGE (h : a < b) : 𝓝[Icc a b] a = 𝓝[≥] a :=
nhdsWithin_inter_of_mem' <| nhdsWithin_le_nhds <| Iic_mem_nhds h
@[deprecated (since := "2024-12-22")]
alias nhdsWithin_Icc_eq_nhdsWithin_Ici := nhdsWithin_Icc_eq_nhdsGE
@[simp]
theorem nhdsWithin_Ico_eq_nhdsGE (h : a < b) : 𝓝[Ico a b] a = 𝓝[≥] a :=
nhdsWithin_inter_of_mem' <| nhdsWithin_le_nhds <| Iio_mem_nhds h
@[deprecated (since := "2024-12-22")]
alias nhdsWithin_Ico_eq_nhdsWithin_Ici := nhdsWithin_Ico_eq_nhdsGE
@[simp]
theorem continuousWithinAt_Icc_iff_Ici (h : a < b) :
ContinuousWithinAt f (Icc a b) a ↔ ContinuousWithinAt f (Ici a) a := by
simp only [ContinuousWithinAt, nhdsWithin_Icc_eq_nhdsGE h]
@[simp]
theorem continuousWithinAt_Ico_iff_Ici (h : a < b) :
ContinuousWithinAt f (Ico a b) a ↔ ContinuousWithinAt f (Ici a) a := by
simp only [ContinuousWithinAt, nhdsWithin_Ico_eq_nhdsGE h]
end LinearOrder
end ClosedIciTopology
section OrderClosedTopology
section Preorder
variable [TopologicalSpace α] [Preorder α] [t : OrderClosedTopology α]
namespace Subtype
-- todo: add `OrderEmbedding.orderClosedTopology`
instance {p : α → Prop} : OrderClosedTopology (Subtype p) :=
have this : Continuous fun p : Subtype p × Subtype p => ((p.fst : α), (p.snd : α)) :=
continuous_subtype_val.prodMap continuous_subtype_val
OrderClosedTopology.mk (t.isClosed_le'.preimage this)
end Subtype
theorem isClosed_le_prod : IsClosed { p : α × α | p.1 ≤ p.2 } :=
t.isClosed_le'
theorem isClosed_le [TopologicalSpace β] {f g : β → α} (hf : Continuous f) (hg : Continuous g) :
IsClosed { b | f b ≤ g b } :=
continuous_iff_isClosed.mp (hf.prodMk hg) _ isClosed_le_prod
instance : ClosedIicTopology α where
isClosed_Iic _ := isClosed_le continuous_id continuous_const
instance : ClosedIciTopology α where
isClosed_Ici _ := isClosed_le continuous_const continuous_id
instance : OrderClosedTopology αᵒᵈ :=
⟨(OrderClosedTopology.isClosed_le' (α := α)).preimage continuous_swap⟩
theorem isClosed_Icc {a b : α} : IsClosed (Icc a b) :=
IsClosed.inter isClosed_Ici isClosed_Iic
@[simp]
theorem closure_Icc (a b : α) : closure (Icc a b) = Icc a b :=
isClosed_Icc.closure_eq
theorem le_of_tendsto_of_tendsto {f g : β → α} {b : Filter β} {a₁ a₂ : α} [NeBot b]
(hf : Tendsto f b (𝓝 a₁)) (hg : Tendsto g b (𝓝 a₂)) (h : f ≤ᶠ[b] g) : a₁ ≤ a₂ :=
have : Tendsto (fun b => (f b, g b)) b (𝓝 (a₁, a₂)) := hf.prodMk_nhds hg
show (a₁, a₂) ∈ { p : α × α | p.1 ≤ p.2 } from t.isClosed_le'.mem_of_tendsto this h
alias tendsto_le_of_eventuallyLE := le_of_tendsto_of_tendsto
theorem le_of_tendsto_of_tendsto' {f g : β → α} {b : Filter β} {a₁ a₂ : α} [NeBot b]
(hf : Tendsto f b (𝓝 a₁)) (hg : Tendsto g b (𝓝 a₂)) (h : ∀ x, f x ≤ g x) : a₁ ≤ a₂ :=
le_of_tendsto_of_tendsto hf hg (Eventually.of_forall h)
@[simp]
theorem closure_le_eq [TopologicalSpace β] {f g : β → α} (hf : Continuous f) (hg : Continuous g) :
closure { b | f b ≤ g b } = { b | f b ≤ g b } :=
(isClosed_le hf hg).closure_eq
theorem closure_lt_subset_le [TopologicalSpace β] {f g : β → α} (hf : Continuous f)
(hg : Continuous g) : closure { b | f b < g b } ⊆ { b | f b ≤ g b } :=
(closure_minimal fun _ => le_of_lt) <| isClosed_le hf hg
theorem ContinuousWithinAt.closure_le [TopologicalSpace β] {f g : β → α} {s : Set β} {x : β}
(hx : x ∈ closure s) (hf : ContinuousWithinAt f s x) (hg : ContinuousWithinAt g s x)
(h : ∀ y ∈ s, f y ≤ g y) : f x ≤ g x :=
show (f x, g x) ∈ { p : α × α | p.1 ≤ p.2 } from
OrderClosedTopology.isClosed_le'.closure_subset ((hf.prodMk hg).mem_closure hx h)
/-- If `s` is a closed set and two functions `f` and `g` are continuous on `s`,
then the set `{x ∈ s | f x ≤ g x}` is a closed set. -/
theorem IsClosed.isClosed_le [TopologicalSpace β] {f g : β → α} {s : Set β} (hs : IsClosed s)
(hf : ContinuousOn f s) (hg : ContinuousOn g s) : IsClosed ({ x ∈ s | f x ≤ g x }) :=
(hf.prodMk hg).preimage_isClosed_of_isClosed hs OrderClosedTopology.isClosed_le'
theorem le_on_closure [TopologicalSpace β] {f g : β → α} {s : Set β} (h : ∀ x ∈ s, f x ≤ g x)
(hf : ContinuousOn f (closure s)) (hg : ContinuousOn g (closure s)) ⦃x⦄ (hx : x ∈ closure s) :
f x ≤ g x :=
have : s ⊆ { y ∈ closure s | f y ≤ g y } := fun y hy => ⟨subset_closure hy, h y hy⟩
(closure_minimal this (isClosed_closure.isClosed_le hf hg) hx).2
theorem IsClosed.epigraph [TopologicalSpace β] {f : β → α} {s : Set β} (hs : IsClosed s)
(hf : ContinuousOn f s) : IsClosed { p : β × α | p.1 ∈ s ∧ f p.1 ≤ p.2 } :=
(hs.preimage continuous_fst).isClosed_le (hf.comp continuousOn_fst Subset.rfl) continuousOn_snd
theorem IsClosed.hypograph [TopologicalSpace β] {f : β → α} {s : Set β} (hs : IsClosed s)
(hf : ContinuousOn f s) : IsClosed { p : β × α | p.1 ∈ s ∧ p.2 ≤ f p.1 } :=
(hs.preimage continuous_fst).isClosed_le continuousOn_snd (hf.comp continuousOn_fst Subset.rfl)
end Preorder
section PartialOrder
variable [TopologicalSpace α] [PartialOrder α] [t : OrderClosedTopology α]
-- see Note [lower instance priority]
instance (priority := 90) OrderClosedTopology.to_t2Space : T2Space α :=
t2_iff_isClosed_diagonal.2 <| by
simpa only [diagonal, le_antisymm_iff] using
t.isClosed_le'.inter (isClosed_le continuous_snd continuous_fst)
end PartialOrder
section LinearOrder
variable [TopologicalSpace α] [LinearOrder α] [OrderClosedTopology α]
theorem isOpen_lt [TopologicalSpace β] {f g : β → α} (hf : Continuous f) (hg : Continuous g) :
IsOpen { b | f b < g b } := by
simpa only [lt_iff_not_le] using (isClosed_le hg hf).isOpen_compl
theorem isOpen_lt_prod : IsOpen { p : α × α | p.1 < p.2 } :=
isOpen_lt continuous_fst continuous_snd
variable {a b : α}
theorem isOpen_Ioo : IsOpen (Ioo a b) :=
IsOpen.inter isOpen_Ioi isOpen_Iio
@[simp]
theorem interior_Ioo : interior (Ioo a b) = Ioo a b :=
isOpen_Ioo.interior_eq
theorem Ioo_subset_closure_interior : Ioo a b ⊆ closure (interior (Ioo a b)) := by
simp only [interior_Ioo, subset_closure]
theorem Ioo_mem_nhds {a b x : α} (ha : a < x) (hb : x < b) : Ioo a b ∈ 𝓝 x :=
IsOpen.mem_nhds isOpen_Ioo ⟨ha, hb⟩
theorem Ioc_mem_nhds {a b x : α} (ha : a < x) (hb : x < b) : Ioc a b ∈ 𝓝 x :=
mem_of_superset (Ioo_mem_nhds ha hb) Ioo_subset_Ioc_self
theorem Ico_mem_nhds {a b x : α} (ha : a < x) (hb : x < b) : Ico a b ∈ 𝓝 x :=
mem_of_superset (Ioo_mem_nhds ha hb) Ioo_subset_Ico_self
theorem Icc_mem_nhds {a b x : α} (ha : a < x) (hb : x < b) : Icc a b ∈ 𝓝 x :=
mem_of_superset (Ioo_mem_nhds ha hb) Ioo_subset_Icc_self
/-- The only order closed topology on a linear order which is a `PredOrder` and a `SuccOrder`
is the discrete topology.
This theorem is not an instance,
because it causes searches for `PredOrder` and `SuccOrder` with their `Preorder` arguments
and very rarely matches. -/
theorem DiscreteTopology.of_predOrder_succOrder [PredOrder α] [SuccOrder α] :
DiscreteTopology α := by
refine discreteTopology_iff_nhds.mpr fun a ↦ ?_
rw [← nhdsWithin_univ, ← Iic_union_Ioi, nhdsWithin_union, PredOrder.nhdsLE, SuccOrder.nhdsGT,
sup_bot_eq]
end LinearOrder
section LinearOrder
variable [TopologicalSpace α] [LinearOrder α] [OrderClosedTopology α] {f g : β → α}
section
variable [TopologicalSpace β]
theorem lt_subset_interior_le (hf : Continuous f) (hg : Continuous g) :
{ b | f b < g b } ⊆ interior { b | f b ≤ g b } :=
(interior_maximal fun _ => le_of_lt) <| isOpen_lt hf hg
theorem frontier_le_subset_eq (hf : Continuous f) (hg : Continuous g) :
frontier { b | f b ≤ g b } ⊆ { b | f b = g b } := by
rw [frontier_eq_closure_inter_closure, closure_le_eq hf hg]
rintro b ⟨hb₁, hb₂⟩
refine le_antisymm hb₁ (closure_lt_subset_le hg hf ?_)
convert hb₂ using 2; simp only [not_le.symm]; rfl
theorem frontier_Iic_subset (a : α) : frontier (Iic a) ⊆ {a} :=
frontier_le_subset_eq (@continuous_id α _) continuous_const
theorem frontier_Ici_subset (a : α) : frontier (Ici a) ⊆ {a} :=
frontier_Iic_subset (α := αᵒᵈ) _
theorem frontier_lt_subset_eq (hf : Continuous f) (hg : Continuous g) :
frontier { b | f b < g b } ⊆ { b | f b = g b } := by
simpa only [← not_lt, ← compl_setOf, frontier_compl, eq_comm] using frontier_le_subset_eq hg hf
| Mathlib/Topology/Order/OrderClosed.lean | 874 | 877 | theorem continuous_if_le [TopologicalSpace γ] [∀ x, Decidable (f x ≤ g x)] {f' g' : β → γ}
(hf : Continuous f) (hg : Continuous g) (hf' : ContinuousOn f' { x | f x ≤ g x })
(hg' : ContinuousOn g' { x | g x ≤ f x }) (hfg : ∀ x, f x = g x → f' x = g' x) :
Continuous fun x => if f x ≤ g x then f' x else g' x := by | |
/-
Copyright (c) 2019 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Lu-Ming Zhang
-/
import Mathlib.Data.Matrix.Invertible
import Mathlib.Data.Matrix.Kronecker
import Mathlib.LinearAlgebra.FiniteDimensional.Basic
import Mathlib.LinearAlgebra.Matrix.Adjugate
import Mathlib.LinearAlgebra.Matrix.SemiringInverse
import Mathlib.LinearAlgebra.Matrix.ToLin
import Mathlib.LinearAlgebra.Matrix.Trace
/-!
# Nonsingular inverses
In this file, we define an inverse for square matrices of invertible determinant.
For matrices that are not square or not of full rank, there is a more general notion of
pseudoinverses which we do not consider here.
The definition of inverse used in this file is the adjugate divided by the determinant.
We show that dividing the adjugate by `det A` (if possible), giving a matrix `A⁻¹` (`nonsing_inv`),
will result in a multiplicative inverse to `A`.
Note that there are at least three different inverses in mathlib:
* `A⁻¹` (`Inv.inv`): alone, this satisfies no properties, although it is usually used in
conjunction with `Group` or `GroupWithZero`. On matrices, this is defined to be zero when no
inverse exists.
* `⅟A` (`invOf`): this is only available in the presence of `[Invertible A]`, which guarantees an
inverse exists.
* `Ring.inverse A`: this is defined on any `MonoidWithZero`, and just like `⁻¹` on matrices, is
defined to be zero when no inverse exists.
We start by working with `Invertible`, and show the main results:
* `Matrix.invertibleOfDetInvertible`
* `Matrix.detInvertibleOfInvertible`
* `Matrix.isUnit_iff_isUnit_det`
* `Matrix.mul_eq_one_comm`
After this we define `Matrix.inv` and show it matches `⅟A` and `Ring.inverse A`.
The rest of the results in the file are then about `A⁻¹`
## References
* https://en.wikipedia.org/wiki/Cramer's_rule#Finding_inverse_matrix
## Tags
matrix inverse, cramer, cramer's rule, adjugate
-/
namespace Matrix
universe u u' v
variable {l : Type*} {m : Type u} {n : Type u'} {α : Type v}
open Matrix Equiv Equiv.Perm Finset
/-! ### Matrices are `Invertible` iff their determinants are -/
section Invertible
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
/-- If `A.det` has a constructive inverse, produce one for `A`. -/
def invertibleOfDetInvertible [Invertible A.det] : Invertible A where
invOf := ⅟ A.det • A.adjugate
mul_invOf_self := by
rw [mul_smul_comm, mul_adjugate, smul_smul, invOf_mul_self, one_smul]
invOf_mul_self := by
rw [smul_mul_assoc, adjugate_mul, smul_smul, invOf_mul_self, one_smul]
theorem invOf_eq [Invertible A.det] [Invertible A] : ⅟ A = ⅟ A.det • A.adjugate := by
letI := invertibleOfDetInvertible A
convert (rfl : ⅟ A = _)
/-- `A.det` is invertible if `A` has a left inverse. -/
def detInvertibleOfLeftInverse (h : B * A = 1) : Invertible A.det where
invOf := B.det
mul_invOf_self := by rw [mul_comm, ← det_mul, h, det_one]
invOf_mul_self := by rw [← det_mul, h, det_one]
/-- `A.det` is invertible if `A` has a right inverse. -/
def detInvertibleOfRightInverse (h : A * B = 1) : Invertible A.det where
invOf := B.det
mul_invOf_self := by rw [← det_mul, h, det_one]
invOf_mul_self := by rw [mul_comm, ← det_mul, h, det_one]
/-- If `A` has a constructive inverse, produce one for `A.det`. -/
def detInvertibleOfInvertible [Invertible A] : Invertible A.det :=
detInvertibleOfLeftInverse A (⅟ A) (invOf_mul_self _)
theorem det_invOf [Invertible A] [Invertible A.det] : (⅟ A).det = ⅟ A.det := by
letI := detInvertibleOfInvertible A
convert (rfl : _ = ⅟ A.det)
/-- Together `Matrix.detInvertibleOfInvertible` and `Matrix.invertibleOfDetInvertible` form an
equivalence, although both sides of the equiv are subsingleton anyway. -/
@[simps]
def invertibleEquivDetInvertible : Invertible A ≃ Invertible A.det where
toFun := @detInvertibleOfInvertible _ _ _ _ _ A
invFun := @invertibleOfDetInvertible _ _ _ _ _ A
left_inv _ := Subsingleton.elim _ _
right_inv _ := Subsingleton.elim _ _
/-- Given a proof that `A.det` has a constructive inverse, lift `A` to `(Matrix n n α)ˣ` -/
def unitOfDetInvertible [Invertible A.det] : (Matrix n n α)ˣ :=
@unitOfInvertible _ _ A (invertibleOfDetInvertible A)
/-- When lowered to a prop, `Matrix.invertibleEquivDetInvertible` forms an `iff`. -/
theorem isUnit_iff_isUnit_det : IsUnit A ↔ IsUnit A.det := by
simp only [← nonempty_invertible_iff_isUnit, (invertibleEquivDetInvertible A).nonempty_congr]
@[simp]
theorem isUnits_det_units (A : (Matrix n n α)ˣ) : IsUnit (A : Matrix n n α).det :=
isUnit_iff_isUnit_det _ |>.mp A.isUnit
/-! #### Variants of the statements above with `IsUnit` -/
theorem isUnit_det_of_invertible [Invertible A] : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfInvertible A)
variable {A B}
theorem isUnit_det_of_left_inverse (h : B * A = 1) : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfLeftInverse _ _ h)
theorem isUnit_det_of_right_inverse (h : A * B = 1) : IsUnit A.det :=
@isUnit_of_invertible _ _ _ (detInvertibleOfRightInverse _ _ h)
theorem det_ne_zero_of_left_inverse [Nontrivial α] (h : B * A = 1) : A.det ≠ 0 :=
(isUnit_det_of_left_inverse h).ne_zero
theorem det_ne_zero_of_right_inverse [Nontrivial α] (h : A * B = 1) : A.det ≠ 0 :=
(isUnit_det_of_right_inverse h).ne_zero
end Invertible
section Inv
variable [Fintype n] [DecidableEq n] [CommRing α]
variable (A : Matrix n n α) (B : Matrix n n α)
theorem isUnit_det_transpose (h : IsUnit A.det) : IsUnit Aᵀ.det := by
rw [det_transpose]
exact h
/-! ### A noncomputable `Inv` instance -/
/-- The inverse of a square matrix, when it is invertible (and zero otherwise). -/
noncomputable instance inv : Inv (Matrix n n α) :=
⟨fun A => Ring.inverse A.det • A.adjugate⟩
theorem inv_def (A : Matrix n n α) : A⁻¹ = Ring.inverse A.det • A.adjugate :=
rfl
theorem nonsing_inv_apply_not_isUnit (h : ¬IsUnit A.det) : A⁻¹ = 0 := by
rw [inv_def, Ring.inverse_non_unit _ h, zero_smul]
theorem nonsing_inv_apply (h : IsUnit A.det) : A⁻¹ = (↑h.unit⁻¹ : α) • A.adjugate := by
rw [inv_def, ← Ring.inverse_unit h.unit, IsUnit.unit_spec]
/-- The nonsingular inverse is the same as `invOf` when `A` is invertible. -/
@[simp]
theorem invOf_eq_nonsing_inv [Invertible A] : ⅟ A = A⁻¹ := by
letI := detInvertibleOfInvertible A
rw [inv_def, Ring.inverse_invertible, invOf_eq]
/-- Coercing the result of `Units.instInv` is the same as coercing first and applying the
nonsingular inverse. -/
@[simp, norm_cast]
theorem coe_units_inv (A : (Matrix n n α)ˣ) : ↑A⁻¹ = (A⁻¹ : Matrix n n α) := by
letI := A.invertible
rw [← invOf_eq_nonsing_inv, invOf_units]
/-- The nonsingular inverse is the same as the general `Ring.inverse`. -/
theorem nonsing_inv_eq_ringInverse : A⁻¹ = Ring.inverse A := by
by_cases h_det : IsUnit A.det
· cases (A.isUnit_iff_isUnit_det.mpr h_det).nonempty_invertible
rw [← invOf_eq_nonsing_inv, Ring.inverse_invertible]
· have h := mt A.isUnit_iff_isUnit_det.mp h_det
rw [Ring.inverse_non_unit _ h, nonsing_inv_apply_not_isUnit A h_det]
@[deprecated (since := "2025-04-22")]
alias nonsing_inv_eq_ring_inverse := nonsing_inv_eq_ringInverse
theorem transpose_nonsing_inv : A⁻¹ᵀ = Aᵀ⁻¹ := by
rw [inv_def, inv_def, transpose_smul, det_transpose, adjugate_transpose]
theorem conjTranspose_nonsing_inv [StarRing α] : A⁻¹ᴴ = Aᴴ⁻¹ := by
rw [inv_def, inv_def, conjTranspose_smul, det_conjTranspose, adjugate_conjTranspose,
Ring.inverse_star]
/-- The `nonsing_inv` of `A` is a right inverse. -/
@[simp]
| Mathlib/LinearAlgebra/Matrix/NonsingularInverse.lean | 205 | 207 | theorem mul_nonsing_inv (h : IsUnit A.det) : A * A⁻¹ = 1 := by | cases (A.isUnit_iff_isUnit_det.mpr h).nonempty_invertible
rw [← invOf_eq_nonsing_inv, mul_invOf_self] |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.CharP.Basic
import Mathlib.Algebra.Module.End
import Mathlib.Algebra.Ring.Prod
import Mathlib.Data.Fintype.Units
import Mathlib.GroupTheory.GroupAction.SubMulAction
import Mathlib.GroupTheory.OrderOfElement
import Mathlib.Tactic.FinCases
/-!
# Integers mod `n`
Definition of the integers mod n, and the field structure on the integers mod p.
## Definitions
* `ZMod n`, which is for integers modulo a nat `n : ℕ`
* `val a` is defined as a natural number:
- for `a : ZMod 0` it is the absolute value of `a`
- for `a : ZMod n` with `0 < n` it is the least natural number in the equivalence class
* A coercion `cast` is defined from `ZMod n` into any ring.
This is a ring hom if the ring has characteristic dividing `n`
-/
assert_not_exists Field Submodule TwoSidedIdeal
open Function ZMod
namespace ZMod
/-- For non-zero `n : ℕ`, the ring `Fin n` is equivalent to `ZMod n`. -/
def finEquiv : ∀ (n : ℕ) [NeZero n], Fin n ≃+* ZMod n
| 0, h => (h.ne _ rfl).elim
| _ + 1, _ => .refl _
instance charZero : CharZero (ZMod 0) := inferInstanceAs (CharZero ℤ)
/-- `val a` is a natural number defined as:
- for `a : ZMod 0` it is the absolute value of `a`
- for `a : ZMod n` with `0 < n` it is the least natural number in the equivalence class
See `ZMod.valMinAbs` for a variant that takes values in the integers.
-/
def val : ∀ {n : ℕ}, ZMod n → ℕ
| 0 => Int.natAbs
| n + 1 => ((↑) : Fin (n + 1) → ℕ)
theorem val_lt {n : ℕ} [NeZero n] (a : ZMod n) : a.val < n := by
cases n
· cases NeZero.ne 0 rfl
exact Fin.is_lt a
theorem val_le {n : ℕ} [NeZero n] (a : ZMod n) : a.val ≤ n :=
a.val_lt.le
@[simp]
theorem val_zero : ∀ {n}, (0 : ZMod n).val = 0
| 0 => rfl
| _ + 1 => rfl
@[simp]
theorem val_one' : (1 : ZMod 0).val = 1 :=
rfl
@[simp]
theorem val_neg' {n : ZMod 0} : (-n).val = n.val :=
Int.natAbs_neg n
@[simp]
theorem val_mul' {m n : ZMod 0} : (m * n).val = m.val * n.val :=
Int.natAbs_mul m n
@[simp]
theorem val_natCast (n a : ℕ) : (a : ZMod n).val = a % n := by
cases n
· rw [Nat.mod_zero]
exact Int.natAbs_natCast a
· apply Fin.val_natCast
lemma val_natCast_of_lt {n a : ℕ} (h : a < n) : (a : ZMod n).val = a := by
rwa [val_natCast, Nat.mod_eq_of_lt]
lemma val_ofNat (n a : ℕ) [a.AtLeastTwo] : (ofNat(a) : ZMod n).val = ofNat(a) % n := val_natCast ..
lemma val_ofNat_of_lt {n a : ℕ} [a.AtLeastTwo] (han : a < n) : (ofNat(a) : ZMod n).val = ofNat(a) :=
val_natCast_of_lt han
theorem val_unit' {n : ZMod 0} : IsUnit n ↔ n.val = 1 := by
simp only [val]
rw [Int.isUnit_iff, Int.natAbs_eq_iff, Nat.cast_one]
lemma eq_one_of_isUnit_natCast {n : ℕ} (h : IsUnit (n : ZMod 0)) : n = 1 := by
rw [← Nat.mod_zero n, ← val_natCast, val_unit'.mp h]
instance charP (n : ℕ) : CharP (ZMod n) n where
cast_eq_zero_iff := by
intro k
rcases n with - | n
· simp [zero_dvd_iff, Int.natCast_eq_zero]
· exact Fin.natCast_eq_zero
@[simp]
theorem addOrderOf_one (n : ℕ) : addOrderOf (1 : ZMod n) = n :=
CharP.eq _ (CharP.addOrderOf_one _) (ZMod.charP n)
/-- This lemma works in the case in which `ZMod n` is not infinite, i.e. `n ≠ 0`. The version
where `a ≠ 0` is `addOrderOf_coe'`. -/
@[simp]
theorem addOrderOf_coe (a : ℕ) {n : ℕ} (n0 : n ≠ 0) : addOrderOf (a : ZMod n) = n / n.gcd a := by
rcases a with - | a
· simp only [Nat.cast_zero, addOrderOf_zero, Nat.gcd_zero_right,
Nat.pos_of_ne_zero n0, Nat.div_self]
rw [← Nat.smul_one_eq_cast, addOrderOf_nsmul' _ a.succ_ne_zero, ZMod.addOrderOf_one]
/-- This lemma works in the case in which `a ≠ 0`. The version where
`ZMod n` is not infinite, i.e. `n ≠ 0`, is `addOrderOf_coe`. -/
@[simp]
theorem addOrderOf_coe' {a : ℕ} (n : ℕ) (a0 : a ≠ 0) : addOrderOf (a : ZMod n) = n / n.gcd a := by
rw [← Nat.smul_one_eq_cast, addOrderOf_nsmul' _ a0, ZMod.addOrderOf_one]
/-- We have that `ringChar (ZMod n) = n`. -/
theorem ringChar_zmod_n (n : ℕ) : ringChar (ZMod n) = n := by
rw [ringChar.eq_iff]
exact ZMod.charP n
theorem natCast_self (n : ℕ) : (n : ZMod n) = 0 :=
CharP.cast_eq_zero (ZMod n) n
@[simp]
theorem natCast_self' (n : ℕ) : (n + 1 : ZMod (n + 1)) = 0 := by
rw [← Nat.cast_add_one, natCast_self (n + 1)]
section UniversalProperty
variable {n : ℕ} {R : Type*}
section
variable [AddGroupWithOne R]
/-- Cast an integer modulo `n` to another semiring.
This function is a morphism if the characteristic of `R` divides `n`.
See `ZMod.castHom` for a bundled version. -/
def cast : ∀ {n : ℕ}, ZMod n → R
| 0 => Int.cast
| _ + 1 => fun i => i.val
@[simp]
theorem cast_zero : (cast (0 : ZMod n) : R) = 0 := by
delta ZMod.cast
cases n
· exact Int.cast_zero
· simp
theorem cast_eq_val [NeZero n] (a : ZMod n) : (cast a : R) = a.val := by
cases n
· cases NeZero.ne 0 rfl
rfl
variable {S : Type*} [AddGroupWithOne S]
@[simp]
theorem _root_.Prod.fst_zmod_cast (a : ZMod n) : (cast a : R × S).fst = cast a := by
cases n
· rfl
· simp [ZMod.cast]
@[simp]
theorem _root_.Prod.snd_zmod_cast (a : ZMod n) : (cast a : R × S).snd = cast a := by
cases n
· rfl
· simp [ZMod.cast]
end
/-- So-named because the coercion is `Nat.cast` into `ZMod`. For `Nat.cast` into an arbitrary ring,
see `ZMod.natCast_val`. -/
theorem natCast_zmod_val {n : ℕ} [NeZero n] (a : ZMod n) : (a.val : ZMod n) = a := by
cases n
· cases NeZero.ne 0 rfl
· apply Fin.cast_val_eq_self
theorem natCast_rightInverse [NeZero n] : Function.RightInverse val ((↑) : ℕ → ZMod n) :=
natCast_zmod_val
theorem natCast_zmod_surjective [NeZero n] : Function.Surjective ((↑) : ℕ → ZMod n) :=
natCast_rightInverse.surjective
/-- So-named because the outer coercion is `Int.cast` into `ZMod`. For `Int.cast` into an arbitrary
ring, see `ZMod.intCast_cast`. -/
@[norm_cast]
theorem intCast_zmod_cast (a : ZMod n) : ((cast a : ℤ) : ZMod n) = a := by
cases n
· simp [ZMod.cast, ZMod]
· dsimp [ZMod.cast]
rw [Int.cast_natCast, natCast_zmod_val]
theorem intCast_rightInverse : Function.RightInverse (cast : ZMod n → ℤ) ((↑) : ℤ → ZMod n) :=
intCast_zmod_cast
theorem intCast_surjective : Function.Surjective ((↑) : ℤ → ZMod n) :=
intCast_rightInverse.surjective
lemma «forall» {P : ZMod n → Prop} : (∀ x, P x) ↔ ∀ x : ℤ, P x := intCast_surjective.forall
lemma «exists» {P : ZMod n → Prop} : (∃ x, P x) ↔ ∃ x : ℤ, P x := intCast_surjective.exists
theorem cast_id : ∀ (n) (i : ZMod n), (ZMod.cast i : ZMod n) = i
| 0, _ => Int.cast_id
| _ + 1, i => natCast_zmod_val i
@[simp]
theorem cast_id' : (ZMod.cast : ZMod n → ZMod n) = id :=
funext (cast_id n)
variable (R) [Ring R]
/-- The coercions are respectively `Nat.cast` and `ZMod.cast`. -/
@[simp]
theorem natCast_comp_val [NeZero n] : ((↑) : ℕ → R) ∘ (val : ZMod n → ℕ) = cast := by
cases n
· cases NeZero.ne 0 rfl
rfl
/-- The coercions are respectively `Int.cast`, `ZMod.cast`, and `ZMod.cast`. -/
@[simp]
theorem intCast_comp_cast : ((↑) : ℤ → R) ∘ (cast : ZMod n → ℤ) = cast := by
cases n
· exact congr_arg (Int.cast ∘ ·) ZMod.cast_id'
· ext
simp [ZMod, ZMod.cast]
variable {R}
@[simp]
theorem natCast_val [NeZero n] (i : ZMod n) : (i.val : R) = cast i :=
congr_fun (natCast_comp_val R) i
@[simp]
theorem intCast_cast (i : ZMod n) : ((cast i : ℤ) : R) = cast i :=
congr_fun (intCast_comp_cast R) i
theorem cast_add_eq_ite {n : ℕ} (a b : ZMod n) :
(cast (a + b) : ℤ) =
if (n : ℤ) ≤ cast a + cast b then (cast a + cast b - n : ℤ) else cast a + cast b := by
rcases n with - | n
· simp; rfl
change Fin (n + 1) at a b
change ((((a + b) : Fin (n + 1)) : ℕ) : ℤ) = if ((n + 1 : ℕ) : ℤ) ≤ (a : ℕ) + b then _ else _
simp only [Fin.val_add_eq_ite, Int.natCast_succ, Int.ofNat_le]
norm_cast
split_ifs with h
· rw [Nat.cast_sub h]
congr
· rfl
section CharDvd
/-! If the characteristic of `R` divides `n`, then `cast` is a homomorphism. -/
variable {m : ℕ} [CharP R m]
@[simp]
theorem cast_one (h : m ∣ n) : (cast (1 : ZMod n) : R) = 1 := by
rcases n with - | n
· exact Int.cast_one
show ((1 % (n + 1) : ℕ) : R) = 1
cases n
· rw [Nat.dvd_one] at h
subst m
subsingleton [CharP.CharOne.subsingleton]
rw [Nat.mod_eq_of_lt]
· exact Nat.cast_one
exact Nat.lt_of_sub_eq_succ rfl
theorem cast_add (h : m ∣ n) (a b : ZMod n) : (cast (a + b : ZMod n) : R) = cast a + cast b := by
cases n
· apply Int.cast_add
symm
dsimp [ZMod, ZMod.cast, ZMod.val]
rw [← Nat.cast_add, Fin.val_add, ← sub_eq_zero, ← Nat.cast_sub (Nat.mod_le _ _),
@CharP.cast_eq_zero_iff R _ m]
exact h.trans (Nat.dvd_sub_mod _)
theorem cast_mul (h : m ∣ n) (a b : ZMod n) : (cast (a * b : ZMod n) : R) = cast a * cast b := by
cases n
· apply Int.cast_mul
symm
dsimp [ZMod, ZMod.cast, ZMod.val]
rw [← Nat.cast_mul, Fin.val_mul, ← sub_eq_zero, ← Nat.cast_sub (Nat.mod_le _ _),
@CharP.cast_eq_zero_iff R _ m]
exact h.trans (Nat.dvd_sub_mod _)
/-- The canonical ring homomorphism from `ZMod n` to a ring of characteristic dividing `n`.
See also `ZMod.lift` for a generalized version working in `AddGroup`s.
-/
def castHom (h : m ∣ n) (R : Type*) [Ring R] [CharP R m] : ZMod n →+* R where
toFun := cast
map_zero' := cast_zero
map_one' := cast_one h
map_add' := cast_add h
map_mul' := cast_mul h
@[simp]
theorem castHom_apply {h : m ∣ n} (i : ZMod n) : castHom h R i = cast i :=
rfl
@[simp]
theorem cast_sub (h : m ∣ n) (a b : ZMod n) : (cast (a - b : ZMod n) : R) = cast a - cast b :=
(castHom h R).map_sub a b
@[simp]
theorem cast_neg (h : m ∣ n) (a : ZMod n) : (cast (-a : ZMod n) : R) = -(cast a) :=
(castHom h R).map_neg a
@[simp]
theorem cast_pow (h : m ∣ n) (a : ZMod n) (k : ℕ) : (cast (a ^ k : ZMod n) : R) = (cast a) ^ k :=
(castHom h R).map_pow a k
@[simp, norm_cast]
theorem cast_natCast (h : m ∣ n) (k : ℕ) : (cast (k : ZMod n) : R) = k :=
map_natCast (castHom h R) k
@[simp, norm_cast]
theorem cast_intCast (h : m ∣ n) (k : ℤ) : (cast (k : ZMod n) : R) = k :=
map_intCast (castHom h R) k
end CharDvd
section CharEq
/-! Some specialised simp lemmas which apply when `R` has characteristic `n`. -/
variable [CharP R n]
@[simp]
theorem cast_one' : (cast (1 : ZMod n) : R) = 1 :=
cast_one dvd_rfl
@[simp]
theorem cast_add' (a b : ZMod n) : (cast (a + b : ZMod n) : R) = cast a + cast b :=
cast_add dvd_rfl a b
@[simp]
theorem cast_mul' (a b : ZMod n) : (cast (a * b : ZMod n) : R) = cast a * cast b :=
cast_mul dvd_rfl a b
@[simp]
theorem cast_sub' (a b : ZMod n) : (cast (a - b : ZMod n) : R) = cast a - cast b :=
cast_sub dvd_rfl a b
@[simp]
theorem cast_pow' (a : ZMod n) (k : ℕ) : (cast (a ^ k : ZMod n) : R) = (cast a : R) ^ k :=
cast_pow dvd_rfl a k
@[simp, norm_cast]
theorem cast_natCast' (k : ℕ) : (cast (k : ZMod n) : R) = k :=
cast_natCast dvd_rfl k
@[simp, norm_cast]
theorem cast_intCast' (k : ℤ) : (cast (k : ZMod n) : R) = k :=
cast_intCast dvd_rfl k
variable (R)
theorem castHom_injective : Function.Injective (ZMod.castHom (dvd_refl n) R) := by
rw [injective_iff_map_eq_zero]
intro x
obtain ⟨k, rfl⟩ := ZMod.intCast_surjective x
rw [map_intCast, CharP.intCast_eq_zero_iff R n, CharP.intCast_eq_zero_iff (ZMod n) n]
exact id
theorem castHom_bijective [Fintype R] (h : Fintype.card R = n) :
Function.Bijective (ZMod.castHom (dvd_refl n) R) := by
haveI : NeZero n :=
⟨by
intro hn
rw [hn] at h
exact (Fintype.card_eq_zero_iff.mp h).elim' 0⟩
rw [Fintype.bijective_iff_injective_and_card, ZMod.card, h, eq_self_iff_true, and_true]
apply ZMod.castHom_injective
/-- The unique ring isomorphism between `ZMod n` and a ring `R`
of characteristic `n` and cardinality `n`. -/
noncomputable def ringEquiv [Fintype R] (h : Fintype.card R = n) : ZMod n ≃+* R :=
RingEquiv.ofBijective _ (ZMod.castHom_bijective R h)
/-- The unique ring isomorphism between `ZMod p` and a ring `R` of cardinality a prime `p`.
If you need any property of this isomorphism, first of all use `ringEquivOfPrime_eq_ringEquiv`
below (after `have : CharP R p := ...`) and deduce it by the results about `ZMod.ringEquiv`. -/
noncomputable def ringEquivOfPrime [Fintype R] {p : ℕ} (hp : p.Prime) (hR : Fintype.card R = p) :
ZMod p ≃+* R :=
have : Nontrivial R := Fintype.one_lt_card_iff_nontrivial.1 (hR ▸ hp.one_lt)
-- The following line exists as `charP_of_card_eq_prime` in `Mathlib.Algebra.CharP.CharAndCard`.
have : CharP R p := (CharP.charP_iff_prime_eq_zero hp).2 (hR ▸ Nat.cast_card_eq_zero R)
ZMod.ringEquiv R hR
@[simp]
lemma ringEquivOfPrime_eq_ringEquiv [Fintype R] {p : ℕ} [CharP R p] (hp : p.Prime)
(hR : Fintype.card R = p) : ringEquivOfPrime R hp hR = ringEquiv R hR := rfl
/-- The identity between `ZMod m` and `ZMod n` when `m = n`, as a ring isomorphism. -/
def ringEquivCongr {m n : ℕ} (h : m = n) : ZMod m ≃+* ZMod n := by
rcases m with - | m <;> rcases n with - | n
· exact RingEquiv.refl _
· exfalso
exact n.succ_ne_zero h.symm
· exfalso
exact m.succ_ne_zero h
· exact
{ finCongr h with
map_mul' := fun a b => by
dsimp [ZMod]
ext
rw [Fin.coe_cast, Fin.coe_mul, Fin.coe_mul, Fin.coe_cast, Fin.coe_cast, ← h]
map_add' := fun a b => by
dsimp [ZMod]
ext
rw [Fin.coe_cast, Fin.val_add, Fin.val_add, Fin.coe_cast, Fin.coe_cast, ← h] }
@[simp] lemma ringEquivCongr_refl (a : ℕ) : ringEquivCongr (rfl : a = a) = .refl _ := by
cases a <;> rfl
lemma ringEquivCongr_refl_apply {a : ℕ} (x : ZMod a) : ringEquivCongr rfl x = x := by
rw [ringEquivCongr_refl]
rfl
lemma ringEquivCongr_symm {a b : ℕ} (hab : a = b) :
(ringEquivCongr hab).symm = ringEquivCongr hab.symm := by
subst hab
cases a <;> rfl
lemma ringEquivCongr_trans {a b c : ℕ} (hab : a = b) (hbc : b = c) :
(ringEquivCongr hab).trans (ringEquivCongr hbc) = ringEquivCongr (hab.trans hbc) := by
subst hab hbc
cases a <;> rfl
lemma ringEquivCongr_ringEquivCongr_apply {a b c : ℕ} (hab : a = b) (hbc : b = c) (x : ZMod a) :
ringEquivCongr hbc (ringEquivCongr hab x) = ringEquivCongr (hab.trans hbc) x := by
rw [← ringEquivCongr_trans hab hbc]
rfl
lemma ringEquivCongr_val {a b : ℕ} (h : a = b) (x : ZMod a) :
ZMod.val ((ZMod.ringEquivCongr h) x) = ZMod.val x := by
subst h
cases a <;> rfl
lemma ringEquivCongr_intCast {a b : ℕ} (h : a = b) (z : ℤ) :
ZMod.ringEquivCongr h z = z := by
subst h
cases a <;> rfl
end CharEq
end UniversalProperty
variable {m n : ℕ}
@[simp]
theorem val_eq_zero : ∀ {n : ℕ} (a : ZMod n), a.val = 0 ↔ a = 0
| 0, _ => Int.natAbs_eq_zero
| n + 1, a => by
rw [Fin.ext_iff]
exact Iff.rfl
theorem intCast_eq_intCast_iff (a b : ℤ) (c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a ≡ b [ZMOD c] :=
CharP.intCast_eq_intCast (ZMod c) c
theorem intCast_eq_intCast_iff' (a b : ℤ) (c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a % c = b % c :=
ZMod.intCast_eq_intCast_iff a b c
theorem val_intCast {n : ℕ} (a : ℤ) [NeZero n] : ↑(a : ZMod n).val = a % n := by
have hle : (0 : ℤ) ≤ ↑(a : ZMod n).val := Int.natCast_nonneg _
have hlt : ↑(a : ZMod n).val < (n : ℤ) := Int.ofNat_lt.mpr (ZMod.val_lt a)
refine (Int.emod_eq_of_lt hle hlt).symm.trans ?_
rw [← ZMod.intCast_eq_intCast_iff', Int.cast_natCast, ZMod.natCast_val, ZMod.cast_id]
theorem natCast_eq_natCast_iff (a b c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a ≡ b [MOD c] := by
simpa [Int.natCast_modEq_iff] using ZMod.intCast_eq_intCast_iff a b c
theorem natCast_eq_natCast_iff' (a b c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a % c = b % c :=
ZMod.natCast_eq_natCast_iff a b c
theorem intCast_zmod_eq_zero_iff_dvd (a : ℤ) (b : ℕ) : (a : ZMod b) = 0 ↔ (b : ℤ) ∣ a := by
rw [← Int.cast_zero, ZMod.intCast_eq_intCast_iff, Int.modEq_zero_iff_dvd]
theorem intCast_eq_intCast_iff_dvd_sub (a b : ℤ) (c : ℕ) : (a : ZMod c) = ↑b ↔ ↑c ∣ b - a := by
rw [ZMod.intCast_eq_intCast_iff, Int.modEq_iff_dvd]
theorem natCast_zmod_eq_zero_iff_dvd (a b : ℕ) : (a : ZMod b) = 0 ↔ b ∣ a := by
rw [← Nat.cast_zero, ZMod.natCast_eq_natCast_iff, Nat.modEq_zero_iff_dvd]
theorem coe_intCast (a : ℤ) : cast (a : ZMod n) = a % n := by
cases n
· rw [Int.ofNat_zero, Int.emod_zero, Int.cast_id]; rfl
· rw [← val_intCast, val]; rfl
lemma intCast_cast_add (x y : ZMod n) : (cast (x + y) : ℤ) = (cast x + cast y) % n := by
rw [← ZMod.coe_intCast, Int.cast_add, ZMod.intCast_zmod_cast, ZMod.intCast_zmod_cast]
lemma intCast_cast_mul (x y : ZMod n) : (cast (x * y) : ℤ) = cast x * cast y % n := by
rw [← ZMod.coe_intCast, Int.cast_mul, ZMod.intCast_zmod_cast, ZMod.intCast_zmod_cast]
lemma intCast_cast_sub (x y : ZMod n) : (cast (x - y) : ℤ) = (cast x - cast y) % n := by
rw [← ZMod.coe_intCast, Int.cast_sub, ZMod.intCast_zmod_cast, ZMod.intCast_zmod_cast]
lemma intCast_cast_neg (x : ZMod n) : (cast (-x) : ℤ) = -cast x % n := by
rw [← ZMod.coe_intCast, Int.cast_neg, ZMod.intCast_zmod_cast]
@[simp]
theorem val_neg_one (n : ℕ) : (-1 : ZMod n.succ).val = n := by
dsimp [val, Fin.coe_neg]
cases n
· simp [Nat.mod_one]
· dsimp [ZMod, ZMod.cast]
rw [Fin.coe_neg_one]
/-- `-1 : ZMod n` lifts to `n - 1 : R`. This avoids the characteristic assumption in `cast_neg`. -/
theorem cast_neg_one {R : Type*} [Ring R] (n : ℕ) : cast (-1 : ZMod n) = (n - 1 : R) := by
rcases n with - | n
· dsimp [ZMod, ZMod.cast]; simp
· rw [← natCast_val, val_neg_one, Nat.cast_succ, add_sub_cancel_right]
theorem cast_sub_one {R : Type*} [Ring R] {n : ℕ} (k : ZMod n) :
(cast (k - 1 : ZMod n) : R) = (if k = 0 then (n : R) else cast k) - 1 := by
split_ifs with hk
· rw [hk, zero_sub, ZMod.cast_neg_one]
· cases n
· dsimp [ZMod, ZMod.cast]
rw [Int.cast_sub, Int.cast_one]
· dsimp [ZMod, ZMod.cast, ZMod.val]
rw [Fin.coe_sub_one, if_neg]
· rw [Nat.cast_sub, Nat.cast_one]
rwa [Fin.ext_iff, Fin.val_zero, ← Ne, ← Nat.one_le_iff_ne_zero] at hk
· exact hk
theorem natCast_eq_iff (p : ℕ) (n : ℕ) (z : ZMod p) [NeZero p] :
↑n = z ↔ ∃ k, n = z.val + p * k := by
constructor
· rintro rfl
refine ⟨n / p, ?_⟩
rw [val_natCast, Nat.mod_add_div]
· rintro ⟨k, rfl⟩
rw [Nat.cast_add, natCast_zmod_val, Nat.cast_mul, natCast_self, zero_mul,
add_zero]
theorem intCast_eq_iff (p : ℕ) (n : ℤ) (z : ZMod p) [NeZero p] :
↑n = z ↔ ∃ k, n = z.val + p * k := by
constructor
· rintro rfl
refine ⟨n / p, ?_⟩
rw [val_intCast, Int.emod_add_ediv]
· rintro ⟨k, rfl⟩
rw [Int.cast_add, Int.cast_mul, Int.cast_natCast, Int.cast_natCast, natCast_val,
ZMod.natCast_self, zero_mul, add_zero, cast_id]
@[push_cast, simp]
theorem intCast_mod (a : ℤ) (b : ℕ) : ((a % b : ℤ) : ZMod b) = (a : ZMod b) := by
rw [ZMod.intCast_eq_intCast_iff]
apply Int.mod_modEq
theorem ker_intCastAddHom (n : ℕ) :
(Int.castAddHom (ZMod n)).ker = AddSubgroup.zmultiples (n : ℤ) := by
ext
rw [Int.mem_zmultiples_iff, AddMonoidHom.mem_ker, Int.coe_castAddHom,
intCast_zmod_eq_zero_iff_dvd]
theorem cast_injective_of_le {m n : ℕ} [nzm : NeZero m] (h : m ≤ n) :
Function.Injective (@cast (ZMod n) _ m) := by
cases m with
| zero => cases nzm; simp_all
| succ m =>
rintro ⟨x, hx⟩ ⟨y, hy⟩ f
simp only [cast, val, natCast_eq_natCast_iff',
Nat.mod_eq_of_lt (hx.trans_le h), Nat.mod_eq_of_lt (hy.trans_le h)] at f
apply Fin.ext
exact f
theorem cast_zmod_eq_zero_iff_of_le {m n : ℕ} [NeZero m] (h : m ≤ n) (a : ZMod m) :
(cast a : ZMod n) = 0 ↔ a = 0 := by
rw [← ZMod.cast_zero (n := m)]
exact Injective.eq_iff' (cast_injective_of_le h) rfl
@[simp]
theorem natCast_toNat (p : ℕ) : ∀ {z : ℤ} (_h : 0 ≤ z), (z.toNat : ZMod p) = z
| (n : ℕ), _h => by simp only [Int.cast_natCast, Int.toNat_natCast]
| Int.negSucc n, h => by simp at h
theorem val_injective (n : ℕ) [NeZero n] : Function.Injective (val : ZMod n → ℕ) := by
cases n
· cases NeZero.ne 0 rfl
intro a b h
dsimp [ZMod]
ext
exact h
theorem val_one_eq_one_mod (n : ℕ) : (1 : ZMod n).val = 1 % n := by
rw [← Nat.cast_one, val_natCast]
theorem val_two_eq_two_mod (n : ℕ) : (2 : ZMod n).val = 2 % n := by
rw [← Nat.cast_two, val_natCast]
theorem val_one (n : ℕ) [Fact (1 < n)] : (1 : ZMod n).val = 1 := by
rw [val_one_eq_one_mod]
exact Nat.mod_eq_of_lt Fact.out
lemma val_one'' : ∀ {n}, n ≠ 1 → (1 : ZMod n).val = 1
| 0, _ => rfl
| 1, hn => by cases hn rfl
| n + 2, _ =>
haveI : Fact (1 < n + 2) := ⟨by simp⟩
ZMod.val_one _
theorem val_add {n : ℕ} [NeZero n] (a b : ZMod n) : (a + b).val = (a.val + b.val) % n := by
cases n
· cases NeZero.ne 0 rfl
· apply Fin.val_add
theorem val_add_of_lt {n : ℕ} {a b : ZMod n} (h : a.val + b.val < n) :
(a + b).val = a.val + b.val := by
have : NeZero n := by constructor; rintro rfl; simp at h
rw [ZMod.val_add, Nat.mod_eq_of_lt h]
theorem val_add_val_of_le {n : ℕ} [NeZero n] {a b : ZMod n} (h : n ≤ a.val + b.val) :
a.val + b.val = (a + b).val + n := by
rw [val_add, Nat.add_mod_add_of_le_add_mod, Nat.mod_eq_of_lt (val_lt _),
Nat.mod_eq_of_lt (val_lt _)]
rwa [Nat.mod_eq_of_lt (val_lt _), Nat.mod_eq_of_lt (val_lt _)]
theorem val_add_of_le {n : ℕ} [NeZero n] {a b : ZMod n} (h : n ≤ a.val + b.val) :
(a + b).val = a.val + b.val - n := by
rw [val_add_val_of_le h]
exact eq_tsub_of_add_eq rfl
theorem val_add_le {n : ℕ} (a b : ZMod n) : (a + b).val ≤ a.val + b.val := by
cases n
· simpa [ZMod.val] using Int.natAbs_add_le _ _
· simpa [ZMod.val_add] using Nat.mod_le _ _
theorem val_mul {n : ℕ} (a b : ZMod n) : (a * b).val = a.val * b.val % n := by
cases n
· rw [Nat.mod_zero]
apply Int.natAbs_mul
· apply Fin.val_mul
theorem val_mul_le {n : ℕ} (a b : ZMod n) : (a * b).val ≤ a.val * b.val := by
rw [val_mul]
apply Nat.mod_le
theorem val_mul_of_lt {n : ℕ} {a b : ZMod n} (h : a.val * b.val < n) :
(a * b).val = a.val * b.val := by
rw [val_mul]
apply Nat.mod_eq_of_lt h
theorem val_mul_iff_lt {n : ℕ} [NeZero n] (a b : ZMod n) :
(a * b).val = a.val * b.val ↔ a.val * b.val < n := by
constructor <;> intro h
· rw [← h]; apply ZMod.val_lt
· apply ZMod.val_mul_of_lt h
instance nontrivial (n : ℕ) [Fact (1 < n)] : Nontrivial (ZMod n) :=
⟨⟨0, 1, fun h =>
zero_ne_one <|
calc
0 = (0 : ZMod n).val := by rw [val_zero]
_ = (1 : ZMod n).val := congr_arg ZMod.val h
_ = 1 := val_one n
⟩⟩
instance nontrivial' : Nontrivial (ZMod 0) := by
delta ZMod; infer_instance
lemma one_eq_zero_iff {n : ℕ} : (1 : ZMod n) = 0 ↔ n = 1 := by
rw [← Nat.cast_one, natCast_zmod_eq_zero_iff_dvd, Nat.dvd_one]
/-- The inversion on `ZMod n`.
It is setup in such a way that `a * a⁻¹` is equal to `gcd a.val n`.
In particular, if `a` is coprime to `n`, and hence a unit, `a * a⁻¹ = 1`. -/
def inv : ∀ n : ℕ, ZMod n → ZMod n
| 0, i => Int.sign i
| n + 1, i => Nat.gcdA i.val (n + 1)
instance (n : ℕ) : Inv (ZMod n) :=
⟨inv n⟩
theorem inv_zero : ∀ n : ℕ, (0 : ZMod n)⁻¹ = 0
| 0 => Int.sign_zero
| n + 1 =>
show (Nat.gcdA _ (n + 1) : ZMod (n + 1)) = 0 by
rw [val_zero]
unfold Nat.gcdA Nat.xgcd Nat.xgcdAux
rfl
theorem mul_inv_eq_gcd {n : ℕ} (a : ZMod n) : a * a⁻¹ = Nat.gcd a.val n := by
rcases n with - | n
· dsimp [ZMod] at a ⊢
calc
_ = a * Int.sign a := rfl
_ = a.natAbs := by rw [Int.mul_sign_self]
_ = a.natAbs.gcd 0 := by rw [Nat.gcd_zero_right]
· calc
a * a⁻¹ = a * a⁻¹ + n.succ * Nat.gcdB (val a) n.succ := by
rw [natCast_self, zero_mul, add_zero]
_ = ↑(↑a.val * Nat.gcdA (val a) n.succ + n.succ * Nat.gcdB (val a) n.succ) := by
push_cast
rw [natCast_zmod_val]
rfl
_ = Nat.gcd a.val n.succ := by rw [← Nat.gcd_eq_gcd_ab a.val n.succ]; rfl
@[simp] protected lemma inv_one (n : ℕ) : (1⁻¹ : ZMod n) = 1 := by
obtain rfl | hn := eq_or_ne n 1
· exact Subsingleton.elim _ _
· simpa [ZMod.val_one'' hn] using mul_inv_eq_gcd (1 : ZMod n)
@[simp]
theorem natCast_mod (a : ℕ) (n : ℕ) : ((a % n : ℕ) : ZMod n) = a := by
conv =>
rhs
rw [← Nat.mod_add_div a n]
simp
theorem eq_iff_modEq_nat (n : ℕ) {a b : ℕ} : (a : ZMod n) = b ↔ a ≡ b [MOD n] := by
cases n
· simp [Nat.ModEq, Int.natCast_inj, Nat.mod_zero]
· rw [Fin.ext_iff, Nat.ModEq, ← val_natCast, ← val_natCast]
exact Iff.rfl
theorem eq_zero_iff_even {n : ℕ} : (n : ZMod 2) = 0 ↔ Even n :=
(CharP.cast_eq_zero_iff (ZMod 2) 2 n).trans even_iff_two_dvd.symm
theorem eq_one_iff_odd {n : ℕ} : (n : ZMod 2) = 1 ↔ Odd n := by
rw [← @Nat.cast_one (ZMod 2), ZMod.eq_iff_modEq_nat, Nat.odd_iff, Nat.ModEq]
| Mathlib/Data/ZMod/Basic.lean | 746 | 747 | theorem ne_zero_iff_odd {n : ℕ} : (n : ZMod 2) ≠ 0 ↔ Odd n := by | constructor <;> |
/-
Copyright (c) 2019 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Yury Kudryashov
-/
import Mathlib.Data.Set.Lattice.Image
import Mathlib.Order.Interval.Set.LinearOrder
/-!
# Extra lemmas about intervals
This file contains lemmas about intervals that cannot be included into `Order.Interval.Set.Basic`
because this would create an `import` cycle. Namely, lemmas in this file can use definitions
from `Data.Set.Lattice`, including `Disjoint`.
We consider various intersections and unions of half infinite intervals.
-/
universe u v w
variable {ι : Sort u} {α : Type v} {β : Type w}
open Set
open OrderDual (toDual)
namespace Set
section Preorder
variable [Preorder α] {a b c : α}
@[simp]
theorem Iic_disjoint_Ioi (h : a ≤ b) : Disjoint (Iic a) (Ioi b) :=
disjoint_left.mpr fun _ ha hb => (h.trans_lt hb).not_le ha
@[simp]
theorem Iio_disjoint_Ici (h : a ≤ b) : Disjoint (Iio a) (Ici b) :=
disjoint_left.mpr fun _ ha hb => (h.trans_lt' ha).not_le hb
@[simp]
theorem Iic_disjoint_Ioc (h : a ≤ b) : Disjoint (Iic a) (Ioc b c) :=
(Iic_disjoint_Ioi h).mono le_rfl Ioc_subset_Ioi_self
@[simp]
theorem Ioc_disjoint_Ioc_of_le {d : α} (h : b ≤ c) : Disjoint (Ioc a b) (Ioc c d) :=
(Iic_disjoint_Ioc h).mono Ioc_subset_Iic_self le_rfl
@[deprecated Ioc_disjoint_Ioc_of_le (since := "2025-03-04")]
theorem Ioc_disjoint_Ioc_same : Disjoint (Ioc a b) (Ioc b c) :=
(Iic_disjoint_Ioc le_rfl).mono Ioc_subset_Iic_self le_rfl
@[simp]
theorem Ico_disjoint_Ico_same : Disjoint (Ico a b) (Ico b c) :=
disjoint_left.mpr fun _ hab hbc => hab.2.not_le hbc.1
@[simp]
theorem Ici_disjoint_Iic : Disjoint (Ici a) (Iic b) ↔ ¬a ≤ b := by
rw [Set.disjoint_iff_inter_eq_empty, Ici_inter_Iic, Icc_eq_empty_iff]
@[simp]
theorem Iic_disjoint_Ici : Disjoint (Iic a) (Ici b) ↔ ¬b ≤ a :=
disjoint_comm.trans Ici_disjoint_Iic
@[simp]
theorem Ioc_disjoint_Ioi (h : b ≤ c) : Disjoint (Ioc a b) (Ioi c) :=
disjoint_left.mpr (fun _ hx hy ↦ (hx.2.trans h).not_lt hy)
theorem Ioc_disjoint_Ioi_same : Disjoint (Ioc a b) (Ioi b) :=
Ioc_disjoint_Ioi le_rfl
@[simp]
theorem iUnion_Iic : ⋃ a : α, Iic a = univ :=
iUnion_eq_univ_iff.2 fun x => ⟨x, right_mem_Iic⟩
@[simp]
theorem iUnion_Ici : ⋃ a : α, Ici a = univ :=
iUnion_eq_univ_iff.2 fun x => ⟨x, left_mem_Ici⟩
@[simp]
theorem iUnion_Icc_right (a : α) : ⋃ b, Icc a b = Ici a := by
simp only [← Ici_inter_Iic, ← inter_iUnion, iUnion_Iic, inter_univ]
@[simp]
theorem iUnion_Ioc_right (a : α) : ⋃ b, Ioc a b = Ioi a := by
simp only [← Ioi_inter_Iic, ← inter_iUnion, iUnion_Iic, inter_univ]
@[simp]
theorem iUnion_Icc_left (b : α) : ⋃ a, Icc a b = Iic b := by
simp only [← Ici_inter_Iic, ← iUnion_inter, iUnion_Ici, univ_inter]
@[simp]
theorem iUnion_Ico_left (b : α) : ⋃ a, Ico a b = Iio b := by
simp only [← Ici_inter_Iio, ← iUnion_inter, iUnion_Ici, univ_inter]
@[simp]
theorem iUnion_Iio [NoMaxOrder α] : ⋃ a : α, Iio a = univ :=
iUnion_eq_univ_iff.2 exists_gt
@[simp]
theorem iUnion_Ioi [NoMinOrder α] : ⋃ a : α, Ioi a = univ :=
iUnion_eq_univ_iff.2 exists_lt
@[simp]
theorem iUnion_Ico_right [NoMaxOrder α] (a : α) : ⋃ b, Ico a b = Ici a := by
simp only [← Ici_inter_Iio, ← inter_iUnion, iUnion_Iio, inter_univ]
@[simp]
theorem iUnion_Ioo_right [NoMaxOrder α] (a : α) : ⋃ b, Ioo a b = Ioi a := by
simp only [← Ioi_inter_Iio, ← inter_iUnion, iUnion_Iio, inter_univ]
@[simp]
theorem iUnion_Ioc_left [NoMinOrder α] (b : α) : ⋃ a, Ioc a b = Iic b := by
simp only [← Ioi_inter_Iic, ← iUnion_inter, iUnion_Ioi, univ_inter]
@[simp]
theorem iUnion_Ioo_left [NoMinOrder α] (b : α) : ⋃ a, Ioo a b = Iio b := by
simp only [← Ioi_inter_Iio, ← iUnion_inter, iUnion_Ioi, univ_inter]
end Preorder
section LinearOrder
variable [LinearOrder α] {a₁ a₂ b₁ b₂ : α}
@[simp]
theorem Ico_disjoint_Ico : Disjoint (Ico a₁ a₂) (Ico b₁ b₂) ↔ min a₂ b₂ ≤ max a₁ b₁ := by
simp_rw [Set.disjoint_iff_inter_eq_empty, Ico_inter_Ico, Ico_eq_empty_iff, not_lt]
@[simp]
theorem Ioc_disjoint_Ioc : Disjoint (Ioc a₁ a₂) (Ioc b₁ b₂) ↔ min a₂ b₂ ≤ max a₁ b₁ := by
have h : _ ↔ min (toDual a₁) (toDual b₁) ≤ max (toDual a₂) (toDual b₂) := Ico_disjoint_Ico
simpa only [Ico_toDual] using h
@[simp]
theorem Ioo_disjoint_Ioo [DenselyOrdered α] :
Disjoint (Set.Ioo a₁ a₂) (Set.Ioo b₁ b₂) ↔ min a₂ b₂ ≤ max a₁ b₁ := by
simp_rw [Set.disjoint_iff_inter_eq_empty, Ioo_inter_Ioo, Ioo_eq_empty_iff, not_lt]
/-- If two half-open intervals are disjoint and the endpoint of one lies in the other,
then it must be equal to the endpoint of the other. -/
theorem eq_of_Ico_disjoint {x₁ x₂ y₁ y₂ : α} (h : Disjoint (Ico x₁ x₂) (Ico y₁ y₂)) (hx : x₁ < x₂)
(h2 : x₂ ∈ Ico y₁ y₂) : y₁ = x₂ := by
rw [Ico_disjoint_Ico, min_eq_left (le_of_lt h2.2), le_max_iff] at h
apply le_antisymm h2.1
exact h.elim (fun h => absurd hx (not_lt_of_le h)) id
@[simp]
theorem iUnion_Ico_eq_Iio_self_iff {f : ι → α} {a : α} :
⋃ i, Ico (f i) a = Iio a ↔ ∀ x < a, ∃ i, f i ≤ x := by
simp [← Ici_inter_Iio, ← iUnion_inter, subset_def]
@[simp]
| Mathlib/Order/Interval/Set/Disjoint.lean | 155 | 158 | theorem iUnion_Ioc_eq_Ioi_self_iff {f : ι → α} {a : α} :
⋃ i, Ioc a (f i) = Ioi a ↔ ∀ x, a < x → ∃ i, x ≤ f i := by | simp [← Ioi_inter_Iic, ← inter_iUnion, subset_def] |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.CharP.Basic
import Mathlib.Algebra.Module.End
import Mathlib.Algebra.Ring.Prod
import Mathlib.Data.Fintype.Units
import Mathlib.GroupTheory.GroupAction.SubMulAction
import Mathlib.GroupTheory.OrderOfElement
import Mathlib.Tactic.FinCases
/-!
# Integers mod `n`
Definition of the integers mod n, and the field structure on the integers mod p.
## Definitions
* `ZMod n`, which is for integers modulo a nat `n : ℕ`
* `val a` is defined as a natural number:
- for `a : ZMod 0` it is the absolute value of `a`
- for `a : ZMod n` with `0 < n` it is the least natural number in the equivalence class
* A coercion `cast` is defined from `ZMod n` into any ring.
This is a ring hom if the ring has characteristic dividing `n`
-/
assert_not_exists Field Submodule TwoSidedIdeal
open Function ZMod
namespace ZMod
/-- For non-zero `n : ℕ`, the ring `Fin n` is equivalent to `ZMod n`. -/
def finEquiv : ∀ (n : ℕ) [NeZero n], Fin n ≃+* ZMod n
| 0, h => (h.ne _ rfl).elim
| _ + 1, _ => .refl _
instance charZero : CharZero (ZMod 0) := inferInstanceAs (CharZero ℤ)
/-- `val a` is a natural number defined as:
- for `a : ZMod 0` it is the absolute value of `a`
- for `a : ZMod n` with `0 < n` it is the least natural number in the equivalence class
See `ZMod.valMinAbs` for a variant that takes values in the integers.
-/
def val : ∀ {n : ℕ}, ZMod n → ℕ
| 0 => Int.natAbs
| n + 1 => ((↑) : Fin (n + 1) → ℕ)
theorem val_lt {n : ℕ} [NeZero n] (a : ZMod n) : a.val < n := by
cases n
· cases NeZero.ne 0 rfl
exact Fin.is_lt a
theorem val_le {n : ℕ} [NeZero n] (a : ZMod n) : a.val ≤ n :=
a.val_lt.le
@[simp]
theorem val_zero : ∀ {n}, (0 : ZMod n).val = 0
| 0 => rfl
| _ + 1 => rfl
@[simp]
theorem val_one' : (1 : ZMod 0).val = 1 :=
rfl
@[simp]
theorem val_neg' {n : ZMod 0} : (-n).val = n.val :=
Int.natAbs_neg n
@[simp]
theorem val_mul' {m n : ZMod 0} : (m * n).val = m.val * n.val :=
Int.natAbs_mul m n
@[simp]
theorem val_natCast (n a : ℕ) : (a : ZMod n).val = a % n := by
cases n
· rw [Nat.mod_zero]
exact Int.natAbs_natCast a
· apply Fin.val_natCast
lemma val_natCast_of_lt {n a : ℕ} (h : a < n) : (a : ZMod n).val = a := by
rwa [val_natCast, Nat.mod_eq_of_lt]
lemma val_ofNat (n a : ℕ) [a.AtLeastTwo] : (ofNat(a) : ZMod n).val = ofNat(a) % n := val_natCast ..
lemma val_ofNat_of_lt {n a : ℕ} [a.AtLeastTwo] (han : a < n) : (ofNat(a) : ZMod n).val = ofNat(a) :=
val_natCast_of_lt han
theorem val_unit' {n : ZMod 0} : IsUnit n ↔ n.val = 1 := by
simp only [val]
rw [Int.isUnit_iff, Int.natAbs_eq_iff, Nat.cast_one]
lemma eq_one_of_isUnit_natCast {n : ℕ} (h : IsUnit (n : ZMod 0)) : n = 1 := by
rw [← Nat.mod_zero n, ← val_natCast, val_unit'.mp h]
instance charP (n : ℕ) : CharP (ZMod n) n where
cast_eq_zero_iff := by
intro k
rcases n with - | n
· simp [zero_dvd_iff, Int.natCast_eq_zero]
· exact Fin.natCast_eq_zero
@[simp]
theorem addOrderOf_one (n : ℕ) : addOrderOf (1 : ZMod n) = n :=
CharP.eq _ (CharP.addOrderOf_one _) (ZMod.charP n)
/-- This lemma works in the case in which `ZMod n` is not infinite, i.e. `n ≠ 0`. The version
where `a ≠ 0` is `addOrderOf_coe'`. -/
@[simp]
theorem addOrderOf_coe (a : ℕ) {n : ℕ} (n0 : n ≠ 0) : addOrderOf (a : ZMod n) = n / n.gcd a := by
rcases a with - | a
· simp only [Nat.cast_zero, addOrderOf_zero, Nat.gcd_zero_right,
Nat.pos_of_ne_zero n0, Nat.div_self]
rw [← Nat.smul_one_eq_cast, addOrderOf_nsmul' _ a.succ_ne_zero, ZMod.addOrderOf_one]
/-- This lemma works in the case in which `a ≠ 0`. The version where
`ZMod n` is not infinite, i.e. `n ≠ 0`, is `addOrderOf_coe`. -/
@[simp]
theorem addOrderOf_coe' {a : ℕ} (n : ℕ) (a0 : a ≠ 0) : addOrderOf (a : ZMod n) = n / n.gcd a := by
rw [← Nat.smul_one_eq_cast, addOrderOf_nsmul' _ a0, ZMod.addOrderOf_one]
/-- We have that `ringChar (ZMod n) = n`. -/
theorem ringChar_zmod_n (n : ℕ) : ringChar (ZMod n) = n := by
rw [ringChar.eq_iff]
exact ZMod.charP n
theorem natCast_self (n : ℕ) : (n : ZMod n) = 0 :=
CharP.cast_eq_zero (ZMod n) n
@[simp]
theorem natCast_self' (n : ℕ) : (n + 1 : ZMod (n + 1)) = 0 := by
rw [← Nat.cast_add_one, natCast_self (n + 1)]
section UniversalProperty
variable {n : ℕ} {R : Type*}
section
variable [AddGroupWithOne R]
/-- Cast an integer modulo `n` to another semiring.
This function is a morphism if the characteristic of `R` divides `n`.
See `ZMod.castHom` for a bundled version. -/
def cast : ∀ {n : ℕ}, ZMod n → R
| 0 => Int.cast
| _ + 1 => fun i => i.val
@[simp]
theorem cast_zero : (cast (0 : ZMod n) : R) = 0 := by
delta ZMod.cast
cases n
· exact Int.cast_zero
· simp
theorem cast_eq_val [NeZero n] (a : ZMod n) : (cast a : R) = a.val := by
cases n
· cases NeZero.ne 0 rfl
rfl
variable {S : Type*} [AddGroupWithOne S]
@[simp]
theorem _root_.Prod.fst_zmod_cast (a : ZMod n) : (cast a : R × S).fst = cast a := by
cases n
· rfl
· simp [ZMod.cast]
@[simp]
theorem _root_.Prod.snd_zmod_cast (a : ZMod n) : (cast a : R × S).snd = cast a := by
cases n
· rfl
· simp [ZMod.cast]
end
/-- So-named because the coercion is `Nat.cast` into `ZMod`. For `Nat.cast` into an arbitrary ring,
see `ZMod.natCast_val`. -/
theorem natCast_zmod_val {n : ℕ} [NeZero n] (a : ZMod n) : (a.val : ZMod n) = a := by
cases n
· cases NeZero.ne 0 rfl
· apply Fin.cast_val_eq_self
theorem natCast_rightInverse [NeZero n] : Function.RightInverse val ((↑) : ℕ → ZMod n) :=
natCast_zmod_val
theorem natCast_zmod_surjective [NeZero n] : Function.Surjective ((↑) : ℕ → ZMod n) :=
natCast_rightInverse.surjective
/-- So-named because the outer coercion is `Int.cast` into `ZMod`. For `Int.cast` into an arbitrary
ring, see `ZMod.intCast_cast`. -/
@[norm_cast]
theorem intCast_zmod_cast (a : ZMod n) : ((cast a : ℤ) : ZMod n) = a := by
cases n
· simp [ZMod.cast, ZMod]
· dsimp [ZMod.cast]
rw [Int.cast_natCast, natCast_zmod_val]
theorem intCast_rightInverse : Function.RightInverse (cast : ZMod n → ℤ) ((↑) : ℤ → ZMod n) :=
intCast_zmod_cast
theorem intCast_surjective : Function.Surjective ((↑) : ℤ → ZMod n) :=
intCast_rightInverse.surjective
lemma «forall» {P : ZMod n → Prop} : (∀ x, P x) ↔ ∀ x : ℤ, P x := intCast_surjective.forall
lemma «exists» {P : ZMod n → Prop} : (∃ x, P x) ↔ ∃ x : ℤ, P x := intCast_surjective.exists
theorem cast_id : ∀ (n) (i : ZMod n), (ZMod.cast i : ZMod n) = i
| 0, _ => Int.cast_id
| _ + 1, i => natCast_zmod_val i
@[simp]
theorem cast_id' : (ZMod.cast : ZMod n → ZMod n) = id :=
funext (cast_id n)
variable (R) [Ring R]
/-- The coercions are respectively `Nat.cast` and `ZMod.cast`. -/
@[simp]
theorem natCast_comp_val [NeZero n] : ((↑) : ℕ → R) ∘ (val : ZMod n → ℕ) = cast := by
cases n
· cases NeZero.ne 0 rfl
rfl
/-- The coercions are respectively `Int.cast`, `ZMod.cast`, and `ZMod.cast`. -/
@[simp]
| Mathlib/Data/ZMod/Basic.lean | 235 | 239 | theorem intCast_comp_cast : ((↑) : ℤ → R) ∘ (cast : ZMod n → ℤ) = cast := by | cases n
· exact congr_arg (Int.cast ∘ ·) ZMod.cast_id'
· ext
simp [ZMod, ZMod.cast] |
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne, Sébastien Gouëzel
-/
import Mathlib.Analysis.Normed.Module.Basic
import Mathlib.MeasureTheory.Function.SimpleFuncDense
/-!
# Strongly measurable and finitely strongly measurable functions
A function `f` is said to be strongly measurable if `f` is the sequential limit of simple functions.
It is said to be finitely strongly measurable with respect to a measure `μ` if the supports
of those simple functions have finite measure.
If the target space has a second countable topology, strongly measurable and measurable are
equivalent.
If the measure is sigma-finite, strongly measurable and finitely strongly measurable are equivalent.
The main property of finitely strongly measurable functions is
`FinStronglyMeasurable.exists_set_sigmaFinite`: there exists a measurable set `t` such that the
function is supported on `t` and `μ.restrict t` is sigma-finite. As a consequence, we can prove some
results for those functions as if the measure was sigma-finite.
We provide a solid API for strongly measurable functions, as a basis for the Bochner integral.
## Main definitions
* `StronglyMeasurable f`: `f : α → β` is the limit of a sequence `fs : ℕ → SimpleFunc α β`.
* `FinStronglyMeasurable f μ`: `f : α → β` is the limit of a sequence `fs : ℕ → SimpleFunc α β`
such that for all `n ∈ ℕ`, the measure of the support of `fs n` is finite.
## References
* [Hytönen, Tuomas, Jan Van Neerven, Mark Veraar, and Lutz Weis. Analysis in Banach spaces.
Springer, 2016.][Hytonen_VanNeerven_Veraar_Wies_2016]
-/
-- Guard against import creep
assert_not_exists InnerProductSpace
open MeasureTheory Filter TopologicalSpace Function Set MeasureTheory.Measure
open ENNReal Topology MeasureTheory NNReal
variable {α β γ ι : Type*} [Countable ι]
namespace MeasureTheory
local infixr:25 " →ₛ " => SimpleFunc
section Definitions
variable [TopologicalSpace β]
/-- A function is `StronglyMeasurable` if it is the limit of simple functions. -/
def StronglyMeasurable [MeasurableSpace α] (f : α → β) : Prop :=
∃ fs : ℕ → α →ₛ β, ∀ x, Tendsto (fun n => fs n x) atTop (𝓝 (f x))
/-- The notation for StronglyMeasurable giving the measurable space instance explicitly. -/
scoped notation "StronglyMeasurable[" m "]" => @MeasureTheory.StronglyMeasurable _ _ _ m
/-- A function is `FinStronglyMeasurable` with respect to a measure if it is the limit of simple
functions with support with finite measure. -/
def FinStronglyMeasurable [Zero β]
{_ : MeasurableSpace α} (f : α → β) (μ : Measure α := by volume_tac) : Prop :=
∃ fs : ℕ → α →ₛ β, (∀ n, μ (support (fs n)) < ∞) ∧ ∀ x, Tendsto (fun n => fs n x) atTop (𝓝 (f x))
end Definitions
open MeasureTheory
/-! ## Strongly measurable functions -/
section StronglyMeasurable
variable {_ : MeasurableSpace α} {μ : Measure α} {f : α → β} {g : ℕ → α} {m : ℕ}
variable [TopologicalSpace β]
theorem SimpleFunc.stronglyMeasurable (f : α →ₛ β) : StronglyMeasurable f :=
⟨fun _ => f, fun _ => tendsto_const_nhds⟩
@[simp, nontriviality]
lemma StronglyMeasurable.of_subsingleton_dom [Subsingleton α] : StronglyMeasurable f :=
⟨fun _ => SimpleFunc.ofFinite f, fun _ => tendsto_const_nhds⟩
@[simp, nontriviality]
lemma StronglyMeasurable.of_subsingleton_cod [Subsingleton β] : StronglyMeasurable f := by
let f_sf : α →ₛ β := ⟨f, fun x => ?_, Set.Subsingleton.finite Set.subsingleton_of_subsingleton⟩
· exact ⟨fun _ => f_sf, fun x => tendsto_const_nhds⟩
· simp [Set.preimage, eq_iff_true_of_subsingleton]
@[deprecated StronglyMeasurable.of_subsingleton_cod (since := "2025-04-09")]
lemma Subsingleton.stronglyMeasurable [Subsingleton β] (f : α → β) : StronglyMeasurable f :=
.of_subsingleton_cod
@[deprecated StronglyMeasurable.of_subsingleton_dom (since := "2025-04-09")]
lemma Subsingleton.stronglyMeasurable' [Subsingleton α] (f : α → β) : StronglyMeasurable f :=
.of_subsingleton_dom
theorem stronglyMeasurable_const {b : β} : StronglyMeasurable fun _ : α => b :=
⟨fun _ => SimpleFunc.const α b, fun _ => tendsto_const_nhds⟩
@[to_additive]
theorem stronglyMeasurable_one [One β] : StronglyMeasurable (1 : α → β) := stronglyMeasurable_const
/-- A version of `stronglyMeasurable_const` that assumes `f x = f y` for all `x, y`.
This version works for functions between empty types. -/
theorem stronglyMeasurable_const' (hf : ∀ x y, f x = f y) : StronglyMeasurable f := by
nontriviality α
inhabit α
convert stronglyMeasurable_const (β := β) using 1
exact funext fun x => hf x default
variable [MeasurableSingletonClass α]
section aux
omit [TopologicalSpace β]
/-- Auxiliary definition for `StronglyMeasurable.of_discrete`. -/
private noncomputable def simpleFuncAux (f : α → β) (g : ℕ → α) : ℕ → SimpleFunc α β
| 0 => .const _ (f (g 0))
| n + 1 => .piecewise {g n} (.singleton _) (.const _ <| f (g n)) (simpleFuncAux f g n)
private lemma simpleFuncAux_eq_of_lt : ∀ n > m, simpleFuncAux f g n (g m) = f (g m)
| _, .refl => by simp [simpleFuncAux]
| _, Nat.le.step (m := n) hmn => by
obtain hnm | hnm := eq_or_ne (g n) (g m) <;>
simp [simpleFuncAux, Set.piecewise_eq_of_not_mem , hnm.symm, simpleFuncAux_eq_of_lt _ hmn]
private lemma simpleFuncAux_eventuallyEq : ∀ᶠ n in atTop, simpleFuncAux f g n (g m) = f (g m) :=
eventually_atTop.2 ⟨_, simpleFuncAux_eq_of_lt⟩
end aux
lemma StronglyMeasurable.of_discrete [Countable α] : StronglyMeasurable f := by
nontriviality α
nontriviality β
obtain ⟨g, hg⟩ := exists_surjective_nat α
exact ⟨simpleFuncAux f g, hg.forall.2 fun m ↦
tendsto_nhds_of_eventually_eq simpleFuncAux_eventuallyEq⟩
@[deprecated StronglyMeasurable.of_discrete (since := "2025-04-09")]
theorem StronglyMeasurable.of_finite [Finite α] : StronglyMeasurable f := .of_discrete
end StronglyMeasurable
namespace StronglyMeasurable
variable {f g : α → β}
section BasicPropertiesInAnyTopologicalSpace
variable [TopologicalSpace β]
/-- A sequence of simple functions such that
`∀ x, Tendsto (fun n => hf.approx n x) atTop (𝓝 (f x))`.
That property is given by `stronglyMeasurable.tendsto_approx`. -/
protected noncomputable def approx {_ : MeasurableSpace α} (hf : StronglyMeasurable f) :
ℕ → α →ₛ β :=
hf.choose
protected theorem tendsto_approx {_ : MeasurableSpace α} (hf : StronglyMeasurable f) :
∀ x, Tendsto (fun n => hf.approx n x) atTop (𝓝 (f x)) :=
hf.choose_spec
/-- Similar to `stronglyMeasurable.approx`, but enforces that the norm of every function in the
sequence is less than `c` everywhere. If `‖f x‖ ≤ c` this sequence of simple functions verifies
`Tendsto (fun n => hf.approxBounded n x) atTop (𝓝 (f x))`. -/
noncomputable def approxBounded {_ : MeasurableSpace α} [Norm β] [SMul ℝ β]
(hf : StronglyMeasurable f) (c : ℝ) : ℕ → SimpleFunc α β := fun n =>
(hf.approx n).map fun x => min 1 (c / ‖x‖) • x
theorem tendsto_approxBounded_of_norm_le {β} {f : α → β} [NormedAddCommGroup β] [NormedSpace ℝ β]
{m : MeasurableSpace α} (hf : StronglyMeasurable[m] f) {c : ℝ} {x : α} (hfx : ‖f x‖ ≤ c) :
Tendsto (fun n => hf.approxBounded c n x) atTop (𝓝 (f x)) := by
have h_tendsto := hf.tendsto_approx x
simp only [StronglyMeasurable.approxBounded, SimpleFunc.coe_map, Function.comp_apply]
by_cases hfx0 : ‖f x‖ = 0
· rw [norm_eq_zero] at hfx0
rw [hfx0] at h_tendsto ⊢
have h_tendsto_norm : Tendsto (fun n => ‖hf.approx n x‖) atTop (𝓝 0) := by
convert h_tendsto.norm
rw [norm_zero]
refine squeeze_zero_norm (fun n => ?_) h_tendsto_norm
calc
‖min 1 (c / ‖hf.approx n x‖) • hf.approx n x‖ =
‖min 1 (c / ‖hf.approx n x‖)‖ * ‖hf.approx n x‖ :=
norm_smul _ _
_ ≤ ‖(1 : ℝ)‖ * ‖hf.approx n x‖ := by
refine mul_le_mul_of_nonneg_right ?_ (norm_nonneg _)
rw [norm_one, Real.norm_of_nonneg]
· exact min_le_left _ _
· exact le_min zero_le_one (div_nonneg ((norm_nonneg _).trans hfx) (norm_nonneg _))
_ = ‖hf.approx n x‖ := by rw [norm_one, one_mul]
rw [← one_smul ℝ (f x)]
refine Tendsto.smul ?_ h_tendsto
have : min 1 (c / ‖f x‖) = 1 := by
rw [min_eq_left_iff, one_le_div (lt_of_le_of_ne (norm_nonneg _) (Ne.symm hfx0))]
exact hfx
nth_rw 2 [this.symm]
refine Tendsto.min tendsto_const_nhds ?_
exact Tendsto.div tendsto_const_nhds h_tendsto.norm hfx0
theorem tendsto_approxBounded_ae {β} {f : α → β} [NormedAddCommGroup β] [NormedSpace ℝ β]
{m m0 : MeasurableSpace α} {μ : Measure α} (hf : StronglyMeasurable[m] f) {c : ℝ}
(hf_bound : ∀ᵐ x ∂μ, ‖f x‖ ≤ c) :
∀ᵐ x ∂μ, Tendsto (fun n => hf.approxBounded c n x) atTop (𝓝 (f x)) := by
filter_upwards [hf_bound] with x hfx using tendsto_approxBounded_of_norm_le hf hfx
theorem norm_approxBounded_le {β} {f : α → β} [SeminormedAddCommGroup β] [NormedSpace ℝ β]
{m : MeasurableSpace α} {c : ℝ} (hf : StronglyMeasurable[m] f) (hc : 0 ≤ c) (n : ℕ) (x : α) :
‖hf.approxBounded c n x‖ ≤ c := by
simp only [StronglyMeasurable.approxBounded, SimpleFunc.coe_map, Function.comp_apply]
refine (norm_smul_le _ _).trans ?_
by_cases h0 : ‖hf.approx n x‖ = 0
· simp only [h0, _root_.div_zero, min_eq_right, zero_le_one, norm_zero, mul_zero]
exact hc
rcases le_total ‖hf.approx n x‖ c with h | h
· rw [min_eq_left _]
· simpa only [norm_one, one_mul] using h
· rwa [one_le_div (lt_of_le_of_ne (norm_nonneg _) (Ne.symm h0))]
· rw [min_eq_right _]
· rw [norm_div, norm_norm, mul_comm, mul_div, div_eq_mul_inv, mul_comm, ← mul_assoc,
inv_mul_cancel₀ h0, one_mul, Real.norm_of_nonneg hc]
· rwa [div_le_one (lt_of_le_of_ne (norm_nonneg _) (Ne.symm h0))]
theorem _root_.stronglyMeasurable_bot_iff [Nonempty β] [T2Space β] :
StronglyMeasurable[⊥] f ↔ ∃ c, f = fun _ => c := by
rcases isEmpty_or_nonempty α with hα | hα
· simp [eq_iff_true_of_subsingleton]
refine ⟨fun hf => ?_, fun hf_eq => ?_⟩
· refine ⟨f hα.some, ?_⟩
let fs := hf.approx
have h_fs_tendsto : ∀ x, Tendsto (fun n => fs n x) atTop (𝓝 (f x)) := hf.tendsto_approx
have : ∀ n, ∃ c, ∀ x, fs n x = c := fun n => SimpleFunc.simpleFunc_bot (fs n)
let cs n := (this n).choose
have h_cs_eq : ∀ n, ⇑(fs n) = fun _ => cs n := fun n => funext (this n).choose_spec
conv at h_fs_tendsto => enter [x, 1, n]; rw [h_cs_eq]
have h_tendsto : Tendsto cs atTop (𝓝 (f hα.some)) := h_fs_tendsto hα.some
ext1 x
exact tendsto_nhds_unique (h_fs_tendsto x) h_tendsto
· obtain ⟨c, rfl⟩ := hf_eq
exact stronglyMeasurable_const
end BasicPropertiesInAnyTopologicalSpace
theorem finStronglyMeasurable_of_set_sigmaFinite [TopologicalSpace β] [Zero β]
{m : MeasurableSpace α} {μ : Measure α} (hf_meas : StronglyMeasurable f) {t : Set α}
(ht : MeasurableSet t) (hft_zero : ∀ x ∈ tᶜ, f x = 0) (htμ : SigmaFinite (μ.restrict t)) :
FinStronglyMeasurable f μ := by
haveI : SigmaFinite (μ.restrict t) := htμ
let S := spanningSets (μ.restrict t)
have hS_meas : ∀ n, MeasurableSet (S n) := measurableSet_spanningSets (μ.restrict t)
let f_approx := hf_meas.approx
let fs n := SimpleFunc.restrict (f_approx n) (S n ∩ t)
have h_fs_t_compl : ∀ n, ∀ x, x ∉ t → fs n x = 0 := by
intro n x hxt
rw [SimpleFunc.restrict_apply _ ((hS_meas n).inter ht)]
refine Set.indicator_of_not_mem ?_ _
simp [hxt]
refine ⟨fs, ?_, fun x => ?_⟩
· simp_rw [SimpleFunc.support_eq, ← Finset.mem_coe]
classical
refine fun n => measure_biUnion_lt_top {y ∈ (fs n).range | y ≠ 0}.finite_toSet fun y hy => ?_
rw [SimpleFunc.restrict_preimage_singleton _ ((hS_meas n).inter ht)]
swap
· letI : (y : β) → Decidable (y = 0) := fun y => Classical.propDecidable _
rw [Finset.mem_coe, Finset.mem_filter] at hy
exact hy.2
refine (measure_mono Set.inter_subset_left).trans_lt ?_
have h_lt_top := measure_spanningSets_lt_top (μ.restrict t) n
rwa [Measure.restrict_apply' ht] at h_lt_top
· by_cases hxt : x ∈ t
swap
· rw [funext fun n => h_fs_t_compl n x hxt, hft_zero x hxt]
exact tendsto_const_nhds
have h : Tendsto (fun n => (f_approx n) x) atTop (𝓝 (f x)) := hf_meas.tendsto_approx x
obtain ⟨n₁, hn₁⟩ : ∃ n, ∀ m, n ≤ m → fs m x = f_approx m x := by
obtain ⟨n, hn⟩ : ∃ n, ∀ m, n ≤ m → x ∈ S m ∩ t := by
rsuffices ⟨n, hn⟩ : ∃ n, ∀ m, n ≤ m → x ∈ S m
· exact ⟨n, fun m hnm => Set.mem_inter (hn m hnm) hxt⟩
rsuffices ⟨n, hn⟩ : ∃ n, x ∈ S n
· exact ⟨n, fun m hnm => monotone_spanningSets (μ.restrict t) hnm hn⟩
rw [← Set.mem_iUnion, iUnion_spanningSets (μ.restrict t)]
trivial
refine ⟨n, fun m hnm => ?_⟩
simp_rw [fs, SimpleFunc.restrict_apply _ ((hS_meas m).inter ht),
Set.indicator_of_mem (hn m hnm)]
rw [tendsto_atTop'] at h ⊢
intro s hs
obtain ⟨n₂, hn₂⟩ := h s hs
refine ⟨max n₁ n₂, fun m hm => ?_⟩
rw [hn₁ m ((le_max_left _ _).trans hm.le)]
exact hn₂ m ((le_max_right _ _).trans hm.le)
/-- If the measure is sigma-finite, all strongly measurable functions are
`FinStronglyMeasurable`. -/
@[aesop 5% apply (rule_sets := [Measurable])]
protected theorem finStronglyMeasurable [TopologicalSpace β] [Zero β] {m0 : MeasurableSpace α}
(hf : StronglyMeasurable f) (μ : Measure α) [SigmaFinite μ] : FinStronglyMeasurable f μ :=
hf.finStronglyMeasurable_of_set_sigmaFinite MeasurableSet.univ (by simp)
(by rwa [Measure.restrict_univ])
/-- A strongly measurable function is measurable. -/
@[aesop 5% apply (rule_sets := [Measurable])]
protected theorem measurable {_ : MeasurableSpace α} [TopologicalSpace β] [PseudoMetrizableSpace β]
[MeasurableSpace β] [BorelSpace β] (hf : StronglyMeasurable f) : Measurable f :=
measurable_of_tendsto_metrizable (fun n => (hf.approx n).measurable)
(tendsto_pi_nhds.mpr hf.tendsto_approx)
/-- A strongly measurable function is almost everywhere measurable. -/
@[aesop 5% apply (rule_sets := [Measurable])]
protected theorem aemeasurable {_ : MeasurableSpace α} [TopologicalSpace β]
[PseudoMetrizableSpace β] [MeasurableSpace β] [BorelSpace β] {μ : Measure α}
(hf : StronglyMeasurable f) : AEMeasurable f μ :=
hf.measurable.aemeasurable
theorem _root_.Continuous.comp_stronglyMeasurable {_ : MeasurableSpace α} [TopologicalSpace β]
[TopologicalSpace γ] {g : β → γ} {f : α → β} (hg : Continuous g) (hf : StronglyMeasurable f) :
StronglyMeasurable fun x => g (f x) :=
⟨fun n => SimpleFunc.map g (hf.approx n), fun x => (hg.tendsto _).comp (hf.tendsto_approx x)⟩
@[to_additive]
nonrec theorem measurableSet_mulSupport {m : MeasurableSpace α} [One β] [TopologicalSpace β]
[MetrizableSpace β] (hf : StronglyMeasurable f) : MeasurableSet (mulSupport f) := by
borelize β
exact measurableSet_mulSupport hf.measurable
protected theorem mono {m m' : MeasurableSpace α} [TopologicalSpace β]
(hf : StronglyMeasurable[m'] f) (h_mono : m' ≤ m) : StronglyMeasurable[m] f := by
let f_approx : ℕ → @SimpleFunc α m β := fun n =>
@SimpleFunc.mk α m β
(hf.approx n)
(fun x => h_mono _ (SimpleFunc.measurableSet_fiber' _ x))
(SimpleFunc.finite_range (hf.approx n))
exact ⟨f_approx, hf.tendsto_approx⟩
protected theorem prodMk {m : MeasurableSpace α} [TopologicalSpace β] [TopologicalSpace γ]
{f : α → β} {g : α → γ} (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) :
StronglyMeasurable fun x => (f x, g x) := by
refine ⟨fun n => SimpleFunc.pair (hf.approx n) (hg.approx n), fun x => ?_⟩
rw [nhds_prod_eq]
exact Tendsto.prodMk (hf.tendsto_approx x) (hg.tendsto_approx x)
@[deprecated (since := "2025-03-05")] protected alias prod_mk := StronglyMeasurable.prodMk
theorem comp_measurable [TopologicalSpace β] {_ : MeasurableSpace α} {_ : MeasurableSpace γ}
{f : α → β} {g : γ → α} (hf : StronglyMeasurable f) (hg : Measurable g) :
StronglyMeasurable (f ∘ g) :=
⟨fun n => SimpleFunc.comp (hf.approx n) g hg, fun x => hf.tendsto_approx (g x)⟩
theorem of_uncurry_left [TopologicalSpace β] {_ : MeasurableSpace α} {_ : MeasurableSpace γ}
{f : α → γ → β} (hf : StronglyMeasurable (uncurry f)) {x : α} : StronglyMeasurable (f x) :=
hf.comp_measurable measurable_prodMk_left
theorem of_uncurry_right [TopologicalSpace β] {_ : MeasurableSpace α} {_ : MeasurableSpace γ}
{f : α → γ → β} (hf : StronglyMeasurable (uncurry f)) {y : γ} :
StronglyMeasurable fun x => f x y :=
hf.comp_measurable measurable_prodMk_right
protected theorem prod_swap {_ : MeasurableSpace α} {_ : MeasurableSpace β} [TopologicalSpace γ]
{f : β × α → γ} (hf : StronglyMeasurable f) :
StronglyMeasurable (fun z : α × β => f z.swap) :=
hf.comp_measurable measurable_swap
protected theorem fst {_ : MeasurableSpace α} [mβ : MeasurableSpace β] [TopologicalSpace γ]
{f : α → γ} (hf : StronglyMeasurable f) :
StronglyMeasurable (fun z : α × β => f z.1) :=
hf.comp_measurable measurable_fst
protected theorem snd [mα : MeasurableSpace α] {_ : MeasurableSpace β} [TopologicalSpace γ]
{f : β → γ} (hf : StronglyMeasurable f) :
StronglyMeasurable (fun z : α × β => f z.2) :=
hf.comp_measurable measurable_snd
section Arithmetic
variable {mα : MeasurableSpace α} [TopologicalSpace β]
@[to_additive (attr := aesop safe 20 apply (rule_sets := [Measurable]))]
protected theorem mul [Mul β] [ContinuousMul β] (hf : StronglyMeasurable f)
(hg : StronglyMeasurable g) : StronglyMeasurable (f * g) :=
⟨fun n => hf.approx n * hg.approx n, fun x => (hf.tendsto_approx x).mul (hg.tendsto_approx x)⟩
@[to_additive (attr := measurability)]
theorem mul_const [Mul β] [ContinuousMul β] (hf : StronglyMeasurable f) (c : β) :
StronglyMeasurable fun x => f x * c :=
hf.mul stronglyMeasurable_const
@[to_additive (attr := measurability)]
theorem const_mul [Mul β] [ContinuousMul β] (hf : StronglyMeasurable f) (c : β) :
StronglyMeasurable fun x => c * f x :=
stronglyMeasurable_const.mul hf
@[to_additive (attr := aesop safe 20 apply (rule_sets := [Measurable])) const_nsmul]
protected theorem pow [Monoid β] [ContinuousMul β] (hf : StronglyMeasurable f) (n : ℕ) :
StronglyMeasurable (f ^ n) :=
⟨fun k => hf.approx k ^ n, fun x => (hf.tendsto_approx x).pow n⟩
@[to_additive (attr := measurability)]
protected theorem inv [Inv β] [ContinuousInv β] (hf : StronglyMeasurable f) :
StronglyMeasurable f⁻¹ :=
⟨fun n => (hf.approx n)⁻¹, fun x => (hf.tendsto_approx x).inv⟩
@[to_additive (attr := aesop safe 20 apply (rule_sets := [Measurable]))]
protected theorem div [Div β] [ContinuousDiv β] (hf : StronglyMeasurable f)
(hg : StronglyMeasurable g) : StronglyMeasurable (f / g) :=
⟨fun n => hf.approx n / hg.approx n, fun x => (hf.tendsto_approx x).div' (hg.tendsto_approx x)⟩
@[to_additive]
theorem mul_iff_right [CommGroup β] [IsTopologicalGroup β] (hf : StronglyMeasurable f) :
StronglyMeasurable (f * g) ↔ StronglyMeasurable g :=
⟨fun h ↦ show g = f * g * f⁻¹ by simp only [mul_inv_cancel_comm] ▸ h.mul hf.inv,
fun h ↦ hf.mul h⟩
@[to_additive]
theorem mul_iff_left [CommGroup β] [IsTopologicalGroup β] (hf : StronglyMeasurable f) :
StronglyMeasurable (g * f) ↔ StronglyMeasurable g :=
mul_comm g f ▸ mul_iff_right hf
@[to_additive (attr := aesop safe 20 apply (rule_sets := [Measurable]))]
protected theorem smul {𝕜} [TopologicalSpace 𝕜] [SMul 𝕜 β] [ContinuousSMul 𝕜 β] {f : α → 𝕜}
{g : α → β} (hf : StronglyMeasurable f) (hg : StronglyMeasurable g) :
StronglyMeasurable fun x => f x • g x :=
continuous_smul.comp_stronglyMeasurable (hf.prodMk hg)
@[to_additive (attr := measurability)]
protected theorem const_smul {𝕜} [SMul 𝕜 β] [ContinuousConstSMul 𝕜 β] (hf : StronglyMeasurable f)
(c : 𝕜) : StronglyMeasurable (c • f) :=
⟨fun n => c • hf.approx n, fun x => (hf.tendsto_approx x).const_smul c⟩
@[to_additive (attr := measurability)]
protected theorem const_smul' {𝕜} [SMul 𝕜 β] [ContinuousConstSMul 𝕜 β] (hf : StronglyMeasurable f)
(c : 𝕜) : StronglyMeasurable fun x => c • f x :=
hf.const_smul c
@[to_additive (attr := measurability)]
protected theorem smul_const {𝕜} [TopologicalSpace 𝕜] [SMul 𝕜 β] [ContinuousSMul 𝕜 β] {f : α → 𝕜}
(hf : StronglyMeasurable f) (c : β) : StronglyMeasurable fun x => f x • c :=
continuous_smul.comp_stronglyMeasurable (hf.prodMk stronglyMeasurable_const)
/-- In a normed vector space, the addition of a measurable function and a strongly measurable
function is measurable. Note that this is not true without further second-countability assumptions
for the addition of two measurable functions. -/
theorem _root_.Measurable.add_stronglyMeasurable
{α E : Type*} {_ : MeasurableSpace α} [AddCancelMonoid E] [TopologicalSpace E]
[MeasurableSpace E] [BorelSpace E] [ContinuousAdd E] [PseudoMetrizableSpace E]
{g f : α → E} (hg : Measurable g) (hf : StronglyMeasurable f) :
Measurable (g + f) := by
rcases hf with ⟨φ, hφ⟩
have : Tendsto (fun n x ↦ g x + φ n x) atTop (𝓝 (g + f)) :=
tendsto_pi_nhds.2 (fun x ↦ tendsto_const_nhds.add (hφ x))
apply measurable_of_tendsto_metrizable (fun n ↦ ?_) this
exact hg.add_simpleFunc _
/-- In a normed vector space, the subtraction of a measurable function and a strongly measurable
function is measurable. Note that this is not true without further second-countability assumptions
for the subtraction of two measurable functions. -/
theorem _root_.Measurable.sub_stronglyMeasurable
{α E : Type*} {_ : MeasurableSpace α} [AddGroup E] [TopologicalSpace E]
[MeasurableSpace E] [BorelSpace E] [ContinuousAdd E] [ContinuousNeg E] [PseudoMetrizableSpace E]
{g f : α → E} (hg : Measurable g) (hf : StronglyMeasurable f) :
Measurable (g - f) := by
rw [sub_eq_add_neg]
exact hg.add_stronglyMeasurable hf.neg
/-- In a normed vector space, the addition of a strongly measurable function and a measurable
function is measurable. Note that this is not true without further second-countability assumptions
for the addition of two measurable functions. -/
theorem _root_.Measurable.stronglyMeasurable_add
{α E : Type*} {_ : MeasurableSpace α} [AddCancelMonoid E] [TopologicalSpace E]
[MeasurableSpace E] [BorelSpace E] [ContinuousAdd E] [PseudoMetrizableSpace E]
{g f : α → E} (hg : Measurable g) (hf : StronglyMeasurable f) :
Measurable (f + g) := by
rcases hf with ⟨φ, hφ⟩
have : Tendsto (fun n x ↦ φ n x + g x) atTop (𝓝 (f + g)) :=
tendsto_pi_nhds.2 (fun x ↦ (hφ x).add tendsto_const_nhds)
apply measurable_of_tendsto_metrizable (fun n ↦ ?_) this
exact hg.simpleFunc_add _
end Arithmetic
section MulAction
variable {M G G₀ : Type*}
variable [TopologicalSpace β]
variable [Monoid M] [MulAction M β] [ContinuousConstSMul M β]
variable [Group G] [MulAction G β] [ContinuousConstSMul G β]
variable [GroupWithZero G₀] [MulAction G₀ β] [ContinuousConstSMul G₀ β]
theorem _root_.stronglyMeasurable_const_smul_iff {m : MeasurableSpace α} (c : G) :
(StronglyMeasurable fun x => c • f x) ↔ StronglyMeasurable f :=
⟨fun h => by simpa only [inv_smul_smul] using h.const_smul' c⁻¹, fun h => h.const_smul c⟩
nonrec theorem _root_.IsUnit.stronglyMeasurable_const_smul_iff {_ : MeasurableSpace α} {c : M}
(hc : IsUnit c) :
(StronglyMeasurable fun x => c • f x) ↔ StronglyMeasurable f :=
let ⟨u, hu⟩ := hc
hu ▸ stronglyMeasurable_const_smul_iff u
theorem _root_.stronglyMeasurable_const_smul_iff₀ {_ : MeasurableSpace α} {c : G₀} (hc : c ≠ 0) :
(StronglyMeasurable fun x => c • f x) ↔ StronglyMeasurable f :=
(IsUnit.mk0 _ hc).stronglyMeasurable_const_smul_iff
end MulAction
section Order
variable [MeasurableSpace α] [TopologicalSpace β]
open Filter
@[aesop safe 20 (rule_sets := [Measurable])]
protected theorem sup [Max β] [ContinuousSup β] (hf : StronglyMeasurable f)
(hg : StronglyMeasurable g) : StronglyMeasurable (f ⊔ g) :=
⟨fun n => hf.approx n ⊔ hg.approx n, fun x =>
(hf.tendsto_approx x).sup_nhds (hg.tendsto_approx x)⟩
@[aesop safe 20 (rule_sets := [Measurable])]
protected theorem inf [Min β] [ContinuousInf β] (hf : StronglyMeasurable f)
(hg : StronglyMeasurable g) : StronglyMeasurable (f ⊓ g) :=
⟨fun n => hf.approx n ⊓ hg.approx n, fun x =>
(hf.tendsto_approx x).inf_nhds (hg.tendsto_approx x)⟩
end Order
/-!
### Big operators: `∏` and `∑`
-/
section Monoid
variable {M : Type*} [Monoid M] [TopologicalSpace M] [ContinuousMul M] {m : MeasurableSpace α}
@[to_additive (attr := measurability)]
| Mathlib/MeasureTheory/Function/StronglyMeasurable/Basic.lean | 540 | 542 | theorem _root_.List.stronglyMeasurable_prod' (l : List (α → M))
(hl : ∀ f ∈ l, StronglyMeasurable f) : StronglyMeasurable l.prod := by | induction' l with f l ihl; · exact stronglyMeasurable_one |
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin Buzzard, Johan Commelin, Patrick Massot
-/
import Mathlib.Algebra.Order.Hom.Monoid
import Mathlib.Algebra.Order.Ring.Basic
import Mathlib.RingTheory.Ideal.Maps
import Mathlib.Tactic.TFAE
/-!
# The basics of valuation theory.
The basic theory of valuations (non-archimedean norms) on a commutative ring,
following T. Wedhorn's unpublished notes “Adic Spaces” ([wedhorn_adic]).
The definition of a valuation we use here is Definition 1.22 of [wedhorn_adic].
A valuation on a ring `R` is a monoid homomorphism `v` to a linearly ordered
commutative monoid with zero, that in addition satisfies the following two axioms:
* `v 0 = 0`
* `∀ x y, v (x + y) ≤ max (v x) (v y)`
`Valuation R Γ₀` is the type of valuations `R → Γ₀`, with a coercion to the underlying
function. If `v` is a valuation from `R` to `Γ₀` then the induced group
homomorphism `Units(R) → Γ₀` is called `unit_map v`.
The equivalence "relation" `IsEquiv v₁ v₂ : Prop` defined in 1.27 of [wedhorn_adic] is not strictly
speaking a relation, because `v₁ : Valuation R Γ₁` and `v₂ : Valuation R Γ₂` might
not have the same type. This corresponds in ZFC to the set-theoretic difficulty
that the class of all valuations (as `Γ₀` varies) on a ring `R` is not a set.
The "relation" is however reflexive, symmetric and transitive in the obvious
sense. Note that we use 1.27(iii) of [wedhorn_adic] as the definition of equivalence.
## Main definitions
* `Valuation R Γ₀`, the type of valuations on `R` with values in `Γ₀`
* `Valuation.IsNontrivial` is the class of non-trivial valuations, namely those for which there
is an element in the ring whose valuation is `≠ 0` and `≠ 1`.
* `Valuation.IsEquiv`, the heterogeneous equivalence relation on valuations
* `Valuation.supp`, the support of a valuation
* `AddValuation R Γ₀`, the type of additive valuations on `R` with values in a
linearly ordered additive commutative group with a top element, `Γ₀`.
## Implementation Details
`AddValuation R Γ₀` is implemented as `Valuation R (Multiplicative Γ₀)ᵒᵈ`.
## Notation
In the `DiscreteValuation` locale:
* `ℕₘ₀` is a shorthand for `WithZero (Multiplicative ℕ)`
* `ℤₘ₀` is a shorthand for `WithZero (Multiplicative ℤ)`
## TODO
If ever someone extends `Valuation`, we should fully comply to the `DFunLike` by migrating the
boilerplate lemmas to `ValuationClass`.
-/
open Function Ideal
noncomputable section
variable {K F R : Type*} [DivisionRing K]
section
variable (F R) (Γ₀ : Type*) [LinearOrderedCommMonoidWithZero Γ₀] [Ring R]
/-- The type of `Γ₀`-valued valuations on `R`.
When you extend this structure, make sure to extend `ValuationClass`. -/
structure Valuation extends R →*₀ Γ₀ where
/-- The valuation of a sum is less than or equal to the maximum of the valuations. -/
map_add_le_max' : ∀ x y, toFun (x + y) ≤ max (toFun x) (toFun y)
/-- `ValuationClass F α β` states that `F` is a type of valuations.
You should also extend this typeclass when you extend `Valuation`. -/
class ValuationClass (F) (R Γ₀ : outParam Type*) [LinearOrderedCommMonoidWithZero Γ₀] [Ring R]
[FunLike F R Γ₀] : Prop
extends MonoidWithZeroHomClass F R Γ₀ where
/-- The valuation of a sum is less than or equal to the maximum of the valuations. -/
map_add_le_max (f : F) (x y : R) : f (x + y) ≤ max (f x) (f y)
export ValuationClass (map_add_le_max)
instance [FunLike F R Γ₀] [ValuationClass F R Γ₀] : CoeTC F (Valuation R Γ₀) :=
⟨fun f =>
{ toFun := f
map_one' := map_one f
map_zero' := map_zero f
map_mul' := map_mul f
map_add_le_max' := map_add_le_max f }⟩
end
namespace Valuation
variable {Γ₀ : Type*}
variable {Γ'₀ : Type*}
variable {Γ''₀ : Type*} [LinearOrderedCommMonoidWithZero Γ''₀]
section Basic
variable [Ring R]
section Monoid
variable [LinearOrderedCommMonoidWithZero Γ₀] [LinearOrderedCommMonoidWithZero Γ'₀]
instance : FunLike (Valuation R Γ₀) R Γ₀ where
coe f := f.toFun
coe_injective' f g h := by
obtain ⟨⟨⟨_,_⟩, _⟩, _⟩ := f
congr
instance : ValuationClass (Valuation R Γ₀) R Γ₀ where
map_mul f := f.map_mul'
map_one f := f.map_one'
map_zero f := f.map_zero'
map_add_le_max f := f.map_add_le_max'
@[simp]
theorem coe_mk (f : R →*₀ Γ₀) (h) : ⇑(Valuation.mk f h) = f := rfl
theorem toFun_eq_coe (v : Valuation R Γ₀) : v.toFun = v := rfl
@[simp]
theorem toMonoidWithZeroHom_coe_eq_coe (v : Valuation R Γ₀) :
(v.toMonoidWithZeroHom : R → Γ₀) = v := rfl
@[ext]
theorem ext {v₁ v₂ : Valuation R Γ₀} (h : ∀ r, v₁ r = v₂ r) : v₁ = v₂ :=
DFunLike.ext _ _ h
variable (v : Valuation R Γ₀)
@[simp, norm_cast]
theorem coe_coe : ⇑(v : R →*₀ Γ₀) = v := rfl
protected theorem map_zero : v 0 = 0 :=
v.map_zero'
protected theorem map_one : v 1 = 1 :=
v.map_one'
protected theorem map_mul : ∀ x y, v (x * y) = v x * v y :=
v.map_mul'
-- Porting note: LHS side simplified so created map_add'
protected theorem map_add : ∀ x y, v (x + y) ≤ max (v x) (v y) :=
v.map_add_le_max'
@[simp]
theorem map_add' : ∀ x y, v (x + y) ≤ v x ∨ v (x + y) ≤ v y := by
intro x y
rw [← le_max_iff, ← ge_iff_le]
apply v.map_add
theorem map_add_le {x y g} (hx : v x ≤ g) (hy : v y ≤ g) : v (x + y) ≤ g :=
le_trans (v.map_add x y) <| max_le hx hy
theorem map_add_lt {x y g} (hx : v x < g) (hy : v y < g) : v (x + y) < g :=
lt_of_le_of_lt (v.map_add x y) <| max_lt hx hy
theorem map_sum_le {ι : Type*} {s : Finset ι} {f : ι → R} {g : Γ₀} (hf : ∀ i ∈ s, v (f i) ≤ g) :
v (∑ i ∈ s, f i) ≤ g := by
classical
refine
Finset.induction_on s (fun _ => v.map_zero ▸ zero_le')
(fun a s has ih hf => ?_) hf
rw [Finset.forall_mem_insert] at hf; rw [Finset.sum_insert has]
exact v.map_add_le hf.1 (ih hf.2)
theorem map_sum_lt {ι : Type*} {s : Finset ι} {f : ι → R} {g : Γ₀} (hg : g ≠ 0)
(hf : ∀ i ∈ s, v (f i) < g) : v (∑ i ∈ s, f i) < g := by
classical
refine
Finset.induction_on s (fun _ => v.map_zero ▸ (zero_lt_iff.2 hg))
(fun a s has ih hf => ?_) hf
rw [Finset.forall_mem_insert] at hf; rw [Finset.sum_insert has]
exact v.map_add_lt hf.1 (ih hf.2)
theorem map_sum_lt' {ι : Type*} {s : Finset ι} {f : ι → R} {g : Γ₀} (hg : 0 < g)
(hf : ∀ i ∈ s, v (f i) < g) : v (∑ i ∈ s, f i) < g :=
v.map_sum_lt (ne_of_gt hg) hf
protected theorem map_pow : ∀ (x) (n : ℕ), v (x ^ n) = v x ^ n :=
v.toMonoidWithZeroHom.toMonoidHom.map_pow
-- The following definition is not an instance, because we have more than one `v` on a given `R`.
-- In addition, type class inference would not be able to infer `v`.
/-- A valuation gives a preorder on the underlying ring. -/
def toPreorder : Preorder R :=
Preorder.lift v
/-- If `v` is a valuation on a division ring then `v(x) = 0` iff `x = 0`. -/
theorem zero_iff [Nontrivial Γ₀] (v : Valuation K Γ₀) {x : K} : v x = 0 ↔ x = 0 :=
map_eq_zero v
theorem ne_zero_iff [Nontrivial Γ₀] (v : Valuation K Γ₀) {x : K} : v x ≠ 0 ↔ x ≠ 0 :=
map_ne_zero v
lemma pos_iff [Nontrivial Γ₀] (v : Valuation K Γ₀) {x : K} : 0 < v x ↔ x ≠ 0 := by
rw [zero_lt_iff, ne_zero_iff]
theorem unit_map_eq (u : Rˣ) : (Units.map (v : R →* Γ₀) u : Γ₀) = v u :=
rfl
theorem ne_zero_of_unit [Nontrivial Γ₀] (v : Valuation K Γ₀) (x : Kˣ) : v x ≠ (0 : Γ₀) := by
simp only [ne_eq, Valuation.zero_iff, Units.ne_zero x, not_false_iff]
theorem ne_zero_of_isUnit [Nontrivial Γ₀] (v : Valuation K Γ₀) (x : K) (hx : IsUnit x) :
v x ≠ (0 : Γ₀) := by
simpa [hx.choose_spec] using ne_zero_of_unit v hx.choose
/-- A ring homomorphism `S → R` induces a map `Valuation R Γ₀ → Valuation S Γ₀`. -/
def comap {S : Type*} [Ring S] (f : S →+* R) (v : Valuation R Γ₀) : Valuation S Γ₀ :=
{ v.toMonoidWithZeroHom.comp f.toMonoidWithZeroHom with
toFun := v ∘ f
map_add_le_max' := fun x y => by simp only [comp_apply, v.map_add, map_add] }
@[simp]
theorem comap_apply {S : Type*} [Ring S] (f : S →+* R) (v : Valuation R Γ₀) (s : S) :
v.comap f s = v (f s) := rfl
@[simp]
theorem comap_id : v.comap (RingHom.id R) = v :=
ext fun _r => rfl
theorem comap_comp {S₁ : Type*} {S₂ : Type*} [Ring S₁] [Ring S₂] (f : S₁ →+* S₂) (g : S₂ →+* R) :
v.comap (g.comp f) = (v.comap g).comap f :=
ext fun _r => rfl
/-- A `≤`-preserving group homomorphism `Γ₀ → Γ'₀` induces a map `Valuation R Γ₀ → Valuation R Γ'₀`.
-/
def map (f : Γ₀ →*₀ Γ'₀) (hf : Monotone f) (v : Valuation R Γ₀) : Valuation R Γ'₀ :=
{ MonoidWithZeroHom.comp f v.toMonoidWithZeroHom with
toFun := f ∘ v
map_add_le_max' := fun r s =>
calc
f (v (r + s)) ≤ f (max (v r) (v s)) := hf (v.map_add r s)
_ = max (f (v r)) (f (v s)) := hf.map_max
}
@[simp]
lemma map_apply (f : Γ₀ →*₀ Γ'₀) (hf : Monotone f) (v : Valuation R Γ₀) (r : R) :
v.map f hf r = f (v r) := rfl
/-- Two valuations on `R` are defined to be equivalent if they induce the same preorder on `R`. -/
def IsEquiv (v₁ : Valuation R Γ₀) (v₂ : Valuation R Γ'₀) : Prop :=
∀ r s, v₁ r ≤ v₁ s ↔ v₂ r ≤ v₂ s
@[simp]
theorem map_neg (x : R) : v (-x) = v x :=
v.toMonoidWithZeroHom.toMonoidHom.map_neg x
theorem map_sub_swap (x y : R) : v (x - y) = v (y - x) :=
v.toMonoidWithZeroHom.toMonoidHom.map_sub_swap x y
theorem map_sub (x y : R) : v (x - y) ≤ max (v x) (v y) :=
calc
v (x - y) = v (x + -y) := by rw [sub_eq_add_neg]
_ ≤ max (v x) (v <| -y) := v.map_add _ _
_ = max (v x) (v y) := by rw [map_neg]
theorem map_sub_le {x y g} (hx : v x ≤ g) (hy : v y ≤ g) : v (x - y) ≤ g := by
rw [sub_eq_add_neg]
exact v.map_add_le hx <| (v.map_neg y).trans_le hy
theorem map_sub_lt {x y : R} {g : Γ₀} (hx : v x < g) (hy : v y < g) : v (x - y) < g := by
rw [sub_eq_add_neg]
exact v.map_add_lt hx <| (v.map_neg y).trans_lt hy
variable {x y : R}
theorem map_add_of_distinct_val (h : v x ≠ v y) : v (x + y) = max (v x) (v y) := by
suffices ¬v (x + y) < max (v x) (v y) from
or_iff_not_imp_right.1 (le_iff_eq_or_lt.1 (v.map_add x y)) this
intro h'
wlog vyx : v y < v x generalizing x y
· refine this h.symm ?_ (h.lt_or_lt.resolve_right vyx)
rwa [add_comm, max_comm]
rw [max_eq_left_of_lt vyx] at h'
apply lt_irrefl (v x)
calc
v x = v (x + y - y) := by simp
_ ≤ max (v <| x + y) (v y) := map_sub _ _ _
_ < v x := max_lt h' vyx
theorem map_add_eq_of_lt_right (h : v x < v y) : v (x + y) = v y :=
(v.map_add_of_distinct_val h.ne).trans (max_eq_right_iff.mpr h.le)
theorem map_add_eq_of_lt_left (h : v y < v x) : v (x + y) = v x := by
rw [add_comm]; exact map_add_eq_of_lt_right _ h
theorem map_sub_eq_of_lt_right (h : v x < v y) : v (x - y) = v y := by
rw [sub_eq_add_neg, map_add_eq_of_lt_right, map_neg]
rwa [map_neg]
open scoped Classical in
theorem map_sum_eq_of_lt {ι : Type*} {s : Finset ι} {f : ι → R} {j : ι}
(hj : j ∈ s) (h0 : v (f j) ≠ 0) (hf : ∀ i ∈ s \ {j}, v (f i) < v (f j)) :
v (∑ i ∈ s, f i) = v (f j) := by
rw [Finset.sum_eq_add_sum_diff_singleton hj]
exact map_add_eq_of_lt_left _ (map_sum_lt _ h0 hf)
theorem map_sub_eq_of_lt_left (h : v y < v x) : v (x - y) = v x := by
rw [sub_eq_add_neg, map_add_eq_of_lt_left]
rwa [map_neg]
theorem map_eq_of_sub_lt (h : v (y - x) < v x) : v y = v x := by
have := Valuation.map_add_of_distinct_val v (ne_of_gt h).symm
rw [max_eq_right (le_of_lt h)] at this
simpa using this
theorem map_one_add_of_lt (h : v x < 1) : v (1 + x) = 1 := by
rw [← v.map_one] at h
simpa only [v.map_one] using v.map_add_eq_of_lt_left h
theorem map_one_sub_of_lt (h : v x < 1) : v (1 - x) = 1 := by
rw [← v.map_one, ← v.map_neg] at h
rw [sub_eq_add_neg 1 x]
simpa only [v.map_one, v.map_neg] using v.map_add_eq_of_lt_left h
/-- An ordered monoid isomorphism `Γ₀ ≃ Γ'₀` induces an equivalence
`Valuation R Γ₀ ≃ Valuation R Γ'₀`. -/
def congr (f : Γ₀ ≃*o Γ'₀) : Valuation R Γ₀ ≃ Valuation R Γ'₀ where
toFun := map f f.toOrderIso.monotone
invFun := map f.symm f.toOrderIso.symm.monotone
left_inv ν := by ext; simp
right_inv ν := by ext; simp
end Monoid
section Group
variable [LinearOrderedCommGroupWithZero Γ₀] (v : Valuation R Γ₀) {x y : R}
theorem map_inv {R : Type*} [DivisionRing R] (v : Valuation R Γ₀) : ∀ x, v x⁻¹ = (v x)⁻¹ :=
map_inv₀ _
theorem map_div {R : Type*} [DivisionRing R] (v : Valuation R Γ₀) : ∀ x y, v (x / y) = v x / v y :=
map_div₀ _
theorem one_lt_val_iff (v : Valuation K Γ₀) {x : K} (h : x ≠ 0) : 1 < v x ↔ v x⁻¹ < 1 := by
simp [inv_lt_one₀ (v.pos_iff.2 h)]
theorem one_le_val_iff (v : Valuation K Γ₀) {x : K} (h : x ≠ 0) : 1 ≤ v x ↔ v x⁻¹ ≤ 1 := by
simp [inv_le_one₀ (v.pos_iff.2 h)]
theorem val_lt_one_iff (v : Valuation K Γ₀) {x : K} (h : x ≠ 0) : v x < 1 ↔ 1 < v x⁻¹ := by
simp [one_lt_inv₀ (v.pos_iff.2 h)]
theorem val_le_one_iff (v : Valuation K Γ₀) {x : K} (h : x ≠ 0) : v x ≤ 1 ↔ 1 ≤ v x⁻¹ := by
simp [one_le_inv₀ (v.pos_iff.2 h)]
theorem val_eq_one_iff (v : Valuation K Γ₀) {x : K} : v x = 1 ↔ v x⁻¹ = 1 := by
by_cases h : x = 0
· simp only [map_inv₀, inv_eq_one]
· simpa only [le_antisymm_iff, And.comm] using and_congr (one_le_val_iff v h) (val_le_one_iff v h)
theorem val_le_one_or_val_inv_lt_one (v : Valuation K Γ₀) (x : K) : v x ≤ 1 ∨ v x⁻¹ < 1 := by
by_cases h : x = 0
· simp only [h, map_zero, zero_le', inv_zero, zero_lt_one, or_self]
· simp only [← one_lt_val_iff v h, le_or_lt]
/--
This theorem is a weaker version of `Valuation.val_le_one_or_val_inv_lt_one`, but more symmetric
in `x` and `x⁻¹`.
-/
theorem val_le_one_or_val_inv_le_one (v : Valuation K Γ₀) (x : K) : v x ≤ 1 ∨ v x⁻¹ ≤ 1 := by
by_cases h : x = 0
· simp only [h, map_zero, zero_le', inv_zero, or_self]
· simp only [← one_le_val_iff v h, le_total]
/-- The subgroup of elements whose valuation is less than a certain unit. -/
def ltAddSubgroup (v : Valuation R Γ₀) (γ : Γ₀ˣ) : AddSubgroup R where
carrier := { x | v x < γ }
zero_mem' := by simp
add_mem' {x y} x_in y_in := lt_of_le_of_lt (v.map_add x y) (max_lt x_in y_in)
neg_mem' x_in := by rwa [Set.mem_setOf, map_neg]
end Group
end Basic
section IsNontrivial
variable [Ring R] [LinearOrderedCommMonoidWithZero Γ₀] (v : Valuation R Γ₀)
/-- A valuation on a ring is nontrivial if there exists an element with valuation
not equal to `0` or `1`. -/
class IsNontrivial : Prop where
exists_val_nontrivial : ∃ x : R, v x ≠ 0 ∧ v x ≠ 1
/-- For fields, being nontrivial is equivalent to the existence of a unit with valuation
not equal to `1`. -/
lemma isNontrivial_iff_exists_unit {K : Type*} [Field K] {w : Valuation K Γ₀} :
w.IsNontrivial ↔ ∃ x : Kˣ, w x ≠ 1 :=
⟨fun ⟨x, hx0, hx1⟩ ↦
have : Nontrivial Γ₀ := ⟨w x, 0, hx0⟩
⟨Units.mk0 x (w.ne_zero_iff.mp hx0), hx1⟩,
fun ⟨x, hx⟩ ↦
have : Nontrivial Γ₀ := ⟨w x, 1, hx⟩
⟨x, w.ne_zero_iff.mpr (Units.ne_zero x), hx⟩⟩
end IsNontrivial
namespace IsEquiv
variable [Ring R] [LinearOrderedCommMonoidWithZero Γ₀] [LinearOrderedCommMonoidWithZero Γ'₀]
{v : Valuation R Γ₀} {v₁ : Valuation R Γ₀} {v₂ : Valuation R Γ'₀} {v₃ : Valuation R Γ''₀}
@[refl]
theorem refl : v.IsEquiv v := fun _ _ => Iff.refl _
@[symm]
theorem symm (h : v₁.IsEquiv v₂) : v₂.IsEquiv v₁ := fun _ _ => Iff.symm (h _ _)
@[trans]
theorem trans (h₁₂ : v₁.IsEquiv v₂) (h₂₃ : v₂.IsEquiv v₃) : v₁.IsEquiv v₃ := fun _ _ =>
Iff.trans (h₁₂ _ _) (h₂₃ _ _)
theorem of_eq {v' : Valuation R Γ₀} (h : v = v') : v.IsEquiv v' := by subst h; rfl
theorem map {v' : Valuation R Γ₀} (f : Γ₀ →*₀ Γ'₀) (hf : Monotone f) (inf : Injective f)
(h : v.IsEquiv v') : (v.map f hf).IsEquiv (v'.map f hf) :=
let H : StrictMono f := hf.strictMono_of_injective inf
fun r s =>
calc
f (v r) ≤ f (v s) ↔ v r ≤ v s := by rw [H.le_iff_le]
_ ↔ v' r ≤ v' s := h r s
_ ↔ f (v' r) ≤ f (v' s) := by rw [H.le_iff_le]
/-- `comap` preserves equivalence. -/
theorem comap {S : Type*} [Ring S] (f : S →+* R) (h : v₁.IsEquiv v₂) :
(v₁.comap f).IsEquiv (v₂.comap f) := fun r s => h (f r) (f s)
theorem val_eq (h : v₁.IsEquiv v₂) {r s : R} : v₁ r = v₁ s ↔ v₂ r = v₂ s := by
simpa only [le_antisymm_iff] using and_congr (h r s) (h s r)
| Mathlib/RingTheory/Valuation/Basic.lean | 447 | 480 | theorem ne_zero (h : v₁.IsEquiv v₂) {r : R} : v₁ r ≠ 0 ↔ v₂ r ≠ 0 := by | have : v₁ r ≠ v₁ 0 ↔ v₂ r ≠ v₂ 0 := not_congr h.val_eq
rwa [v₁.map_zero, v₂.map_zero] at this
end IsEquiv
-- end of namespace
section
theorem isEquiv_of_map_strictMono [LinearOrderedCommMonoidWithZero Γ₀]
[LinearOrderedCommMonoidWithZero Γ'₀] [Ring R] {v : Valuation R Γ₀} (f : Γ₀ →*₀ Γ'₀)
(H : StrictMono f) : IsEquiv (v.map f H.monotone) v := fun _x _y =>
⟨H.le_iff_le.mp, fun h => H.monotone h⟩
theorem isEquiv_iff_val_lt_val [LinearOrderedCommMonoidWithZero Γ₀]
[LinearOrderedCommMonoidWithZero Γ'₀] {v : Valuation K Γ₀} {v' : Valuation K Γ'₀} :
v.IsEquiv v' ↔ ∀ {x y : K}, v x < v y ↔ v' x < v' y := by
simp only [IsEquiv, le_iff_le_iff_lt_iff_lt]
exact forall_comm
alias ⟨IsEquiv.lt_iff_lt, _⟩ := isEquiv_iff_val_lt_val
theorem isEquiv_of_val_le_one [LinearOrderedCommGroupWithZero Γ₀]
[LinearOrderedCommGroupWithZero Γ'₀] {v : Valuation K Γ₀} {v' : Valuation K Γ'₀}
(h : ∀ {x : K}, v x ≤ 1 ↔ v' x ≤ 1) : v.IsEquiv v' := by
intro x y
obtain rfl | hy := eq_or_ne y 0
· simp
· rw [← div_le_one₀, ← v.map_div, h, v'.map_div, div_le_one₀] <;>
rwa [zero_lt_iff, ne_zero_iff]
theorem isEquiv_iff_val_le_one [LinearOrderedCommGroupWithZero Γ₀]
[LinearOrderedCommGroupWithZero Γ'₀] {v : Valuation K Γ₀} {v' : Valuation K Γ'₀} :
v.IsEquiv v' ↔ ∀ {x : K}, v x ≤ 1 ↔ v' x ≤ 1 := |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Yury Kudryashov
-/
import Mathlib.Data.ENNReal.Operations
/-!
# Results about division in extended non-negative reals
This file establishes basic properties related to the inversion and division operations on `ℝ≥0∞`.
For instance, as a consequence of being a `DivInvOneMonoid`, `ℝ≥0∞` inherits a power operation
with integer exponent.
## Main results
A few order isomorphisms are worthy of mention:
- `OrderIso.invENNReal : ℝ≥0∞ ≃o ℝ≥0∞ᵒᵈ`: The map `x ↦ x⁻¹` as an order isomorphism to the dual.
- `orderIsoIicOneBirational : ℝ≥0∞ ≃o Iic (1 : ℝ≥0∞)`: The birational order isomorphism between
`ℝ≥0∞` and the unit interval `Set.Iic (1 : ℝ≥0∞)` given by `x ↦ (x⁻¹ + 1)⁻¹` with inverse
`x ↦ (x⁻¹ - 1)⁻¹`
- `orderIsoIicCoe (a : ℝ≥0) : Iic (a : ℝ≥0∞) ≃o Iic a`: Order isomorphism between an initial
interval in `ℝ≥0∞` and an initial interval in `ℝ≥0` given by the identity map.
- `orderIsoUnitIntervalBirational : ℝ≥0∞ ≃o Icc (0 : ℝ) 1`: An order isomorphism between
the extended nonnegative real numbers and the unit interval. This is `orderIsoIicOneBirational`
composed with the identity order isomorphism between `Iic (1 : ℝ≥0∞)` and `Icc (0 : ℝ) 1`.
-/
assert_not_exists Finset
open Set NNReal
namespace ENNReal
noncomputable section Inv
variable {a b c d : ℝ≥0∞} {r p q : ℝ≥0}
protected theorem div_eq_inv_mul : a / b = b⁻¹ * a := by rw [div_eq_mul_inv, mul_comm]
@[simp] theorem inv_zero : (0 : ℝ≥0∞)⁻¹ = ∞ :=
show sInf { b : ℝ≥0∞ | 1 ≤ 0 * b } = ∞ by simp
@[simp] theorem inv_top : ∞⁻¹ = 0 :=
bot_unique <| le_of_forall_gt_imp_ge_of_dense fun a (h : 0 < a) => sInf_le <| by
simp [*, h.ne', top_mul]
theorem coe_inv_le : (↑r⁻¹ : ℝ≥0∞) ≤ (↑r)⁻¹ :=
le_sInf fun b (hb : 1 ≤ ↑r * b) =>
coe_le_iff.2 <| by
rintro b rfl
apply NNReal.inv_le_of_le_mul
rwa [← coe_mul, ← coe_one, coe_le_coe] at hb
@[simp, norm_cast]
theorem coe_inv (hr : r ≠ 0) : (↑r⁻¹ : ℝ≥0∞) = (↑r)⁻¹ :=
coe_inv_le.antisymm <| sInf_le <| mem_setOf.2 <| by rw [← coe_mul, mul_inv_cancel₀ hr, coe_one]
@[norm_cast]
theorem coe_inv_two : ((2⁻¹ : ℝ≥0) : ℝ≥0∞) = 2⁻¹ := by rw [coe_inv _root_.two_ne_zero, coe_two]
@[simp, norm_cast]
theorem coe_div (hr : r ≠ 0) : (↑(p / r) : ℝ≥0∞) = p / r := by
rw [div_eq_mul_inv, div_eq_mul_inv, coe_mul, coe_inv hr]
lemma coe_div_le : ↑(p / r) ≤ (p / r : ℝ≥0∞) := by
simpa only [div_eq_mul_inv, coe_mul] using mul_le_mul_left' coe_inv_le _
theorem div_zero (h : a ≠ 0) : a / 0 = ∞ := by simp [div_eq_mul_inv, h]
instance : DivInvOneMonoid ℝ≥0∞ :=
{ inferInstanceAs (DivInvMonoid ℝ≥0∞) with
inv_one := by simpa only [coe_inv one_ne_zero, coe_one] using coe_inj.2 inv_one }
protected theorem inv_pow : ∀ {a : ℝ≥0∞} {n : ℕ}, (a ^ n)⁻¹ = a⁻¹ ^ n
| _, 0 => by simp only [pow_zero, inv_one]
| ⊤, n + 1 => by simp [top_pow]
| (a : ℝ≥0), n + 1 => by
rcases eq_or_ne a 0 with (rfl | ha)
· simp [top_pow]
· have := pow_ne_zero (n + 1) ha
norm_cast
rw [inv_pow]
protected theorem mul_inv_cancel (h0 : a ≠ 0) (ht : a ≠ ∞) : a * a⁻¹ = 1 := by
lift a to ℝ≥0 using ht
norm_cast at h0; norm_cast
exact mul_inv_cancel₀ h0
protected theorem inv_mul_cancel (h0 : a ≠ 0) (ht : a ≠ ∞) : a⁻¹ * a = 1 :=
mul_comm a a⁻¹ ▸ ENNReal.mul_inv_cancel h0 ht
/-- See `ENNReal.inv_mul_cancel_left` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma inv_mul_cancel_left' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) :
a⁻¹ * (a * b) = b := by
obtain rfl | ha₀ := eq_or_ne a 0
· simp_all
obtain rfl | ha := eq_or_ne a ⊤
· simp_all
· simp [← mul_assoc, ENNReal.inv_mul_cancel, *]
/-- See `ENNReal.inv_mul_cancel_left'` for a stronger version. -/
protected lemma inv_mul_cancel_left (ha₀ : a ≠ 0) (ha : a ≠ ∞) : a⁻¹ * (a * b) = b :=
ENNReal.inv_mul_cancel_left' (by simp [ha₀]) (by simp [ha])
/-- See `ENNReal.mul_inv_cancel_left` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma mul_inv_cancel_left' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) :
a * (a⁻¹ * b) = b := by
obtain rfl | ha₀ := eq_or_ne a 0
· simp_all
obtain rfl | ha := eq_or_ne a ⊤
· simp_all
· simp [← mul_assoc, ENNReal.mul_inv_cancel, *]
/-- See `ENNReal.mul_inv_cancel_left'` for a stronger version. -/
protected lemma mul_inv_cancel_left (ha₀ : a ≠ 0) (ha : a ≠ ∞) : a * (a⁻¹ * b) = b :=
ENNReal.mul_inv_cancel_left' (by simp [ha₀]) (by simp [ha])
/-- See `ENNReal.mul_inv_cancel_right` for a simpler version assuming `b ≠ 0`, `b ≠ ∞`. -/
protected lemma mul_inv_cancel_right' (hb₀ : b = 0 → a = 0) (hb : b = ∞ → a = 0) :
a * b * b⁻¹ = a := by
obtain rfl | hb₀ := eq_or_ne b 0
· simp_all
obtain rfl | hb := eq_or_ne b ⊤
· simp_all
· simp [mul_assoc, ENNReal.mul_inv_cancel, *]
/-- See `ENNReal.mul_inv_cancel_right'` for a stronger version. -/
protected lemma mul_inv_cancel_right (hb₀ : b ≠ 0) (hb : b ≠ ∞) : a * b * b⁻¹ = a :=
ENNReal.mul_inv_cancel_right' (by simp [hb₀]) (by simp [hb])
/-- See `ENNReal.inv_mul_cancel_right` for a simpler version assuming `b ≠ 0`, `b ≠ ∞`. -/
protected lemma inv_mul_cancel_right' (hb₀ : b = 0 → a = 0) (hb : b = ∞ → a = 0) :
a * b⁻¹ * b = a := by
obtain rfl | hb₀ := eq_or_ne b 0
· simp_all
obtain rfl | hb := eq_or_ne b ⊤
· simp_all
· simp [mul_assoc, ENNReal.inv_mul_cancel, *]
/-- See `ENNReal.inv_mul_cancel_right'` for a stronger version. -/
protected lemma inv_mul_cancel_right (hb₀ : b ≠ 0) (hb : b ≠ ∞) : a * b⁻¹ * b = a :=
ENNReal.inv_mul_cancel_right' (by simp [hb₀]) (by simp [hb])
/-- See `ENNReal.mul_div_cancel_right` for a simpler version assuming `b ≠ 0`, `b ≠ ∞`. -/
protected lemma mul_div_cancel_right' (hb₀ : b = 0 → a = 0) (hb : b = ∞ → a = 0) :
a * b / b = a := ENNReal.mul_inv_cancel_right' hb₀ hb
/-- See `ENNReal.mul_div_cancel_right'` for a stronger version. -/
protected lemma mul_div_cancel_right (hb₀ : b ≠ 0) (hb : b ≠ ∞) : a * b / b = a :=
ENNReal.mul_div_cancel_right' (by simp [hb₀]) (by simp [hb])
/-- See `ENNReal.div_mul_cancel` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma div_mul_cancel' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) : b / a * a = b :=
ENNReal.inv_mul_cancel_right' ha₀ ha
/-- See `ENNReal.div_mul_cancel'` for a stronger version. -/
protected lemma div_mul_cancel (ha₀ : a ≠ 0) (ha : a ≠ ∞) : b / a * a = b :=
ENNReal.div_mul_cancel' (by simp [ha₀]) (by simp [ha])
/-- See `ENNReal.mul_div_cancel` for a simpler version assuming `a ≠ 0`, `a ≠ ∞`. -/
protected lemma mul_div_cancel' (ha₀ : a = 0 → b = 0) (ha : a = ∞ → b = 0) : a * (b / a) = b := by
rw [mul_comm, ENNReal.div_mul_cancel' ha₀ ha]
/-- See `ENNReal.mul_div_cancel'` for a stronger version. -/
protected lemma mul_div_cancel (ha₀ : a ≠ 0) (ha : a ≠ ∞) : a * (b / a) = b :=
ENNReal.mul_div_cancel' (by simp [ha₀]) (by simp [ha])
protected theorem mul_comm_div : a / b * c = a * (c / b) := by
simp only [div_eq_mul_inv, mul_left_comm, mul_comm, mul_assoc]
protected theorem mul_div_right_comm : a * b / c = a / c * b := by
simp only [div_eq_mul_inv, mul_right_comm]
instance : InvolutiveInv ℝ≥0∞ where
inv_inv a := by
by_cases a = 0 <;> cases a <;> simp_all [none_eq_top, some_eq_coe, -coe_inv, (coe_inv _).symm]
@[simp] protected lemma inv_eq_one : a⁻¹ = 1 ↔ a = 1 := by rw [← inv_inj, inv_inv, inv_one]
@[simp] theorem inv_eq_top : a⁻¹ = ∞ ↔ a = 0 := inv_zero ▸ inv_inj
theorem inv_ne_top : a⁻¹ ≠ ∞ ↔ a ≠ 0 := by simp
@[aesop (rule_sets := [finiteness]) safe apply]
protected alias ⟨_, Finiteness.inv_ne_top⟩ := ENNReal.inv_ne_top
@[simp]
theorem inv_lt_top {x : ℝ≥0∞} : x⁻¹ < ∞ ↔ 0 < x := by
simp only [lt_top_iff_ne_top, inv_ne_top, pos_iff_ne_zero]
theorem div_lt_top {x y : ℝ≥0∞} (h1 : x ≠ ∞) (h2 : y ≠ 0) : x / y < ∞ :=
mul_lt_top h1.lt_top (inv_ne_top.mpr h2).lt_top
@[simp]
protected theorem inv_eq_zero : a⁻¹ = 0 ↔ a = ∞ :=
inv_top ▸ inv_inj
protected theorem inv_ne_zero : a⁻¹ ≠ 0 ↔ a ≠ ∞ := by simp
protected theorem div_pos (ha : a ≠ 0) (hb : b ≠ ∞) : 0 < a / b :=
ENNReal.mul_pos ha <| ENNReal.inv_ne_zero.2 hb
protected theorem inv_mul_le_iff {x y z : ℝ≥0∞} (h1 : x ≠ 0) (h2 : x ≠ ∞) :
x⁻¹ * y ≤ z ↔ y ≤ x * z := by
rw [← mul_le_mul_left h1 h2, ← mul_assoc, ENNReal.mul_inv_cancel h1 h2, one_mul]
protected theorem mul_inv_le_iff {x y z : ℝ≥0∞} (h1 : y ≠ 0) (h2 : y ≠ ∞) :
x * y⁻¹ ≤ z ↔ x ≤ z * y := by
rw [mul_comm, ENNReal.inv_mul_le_iff h1 h2, mul_comm]
protected theorem div_le_iff {x y z : ℝ≥0∞} (h1 : y ≠ 0) (h2 : y ≠ ∞) :
x / y ≤ z ↔ x ≤ z * y := by
rw [div_eq_mul_inv, ENNReal.mul_inv_le_iff h1 h2]
protected theorem div_le_iff' {x y z : ℝ≥0∞} (h1 : y ≠ 0) (h2 : y ≠ ∞) :
x / y ≤ z ↔ x ≤ y * z := by
rw [mul_comm, ENNReal.div_le_iff h1 h2]
protected theorem mul_inv {a b : ℝ≥0∞} (ha : a ≠ 0 ∨ b ≠ ∞) (hb : a ≠ ∞ ∨ b ≠ 0) :
(a * b)⁻¹ = a⁻¹ * b⁻¹ := by
induction' b with b
· replace ha : a ≠ 0 := ha.neg_resolve_right rfl
simp [ha]
induction' a with a
· replace hb : b ≠ 0 := coe_ne_zero.1 (hb.neg_resolve_left rfl)
simp [hb]
by_cases h'a : a = 0
· simp only [h'a, top_mul, ENNReal.inv_zero, ENNReal.coe_ne_top, zero_mul, Ne,
not_false_iff, ENNReal.coe_zero, ENNReal.inv_eq_zero]
by_cases h'b : b = 0
· simp only [h'b, ENNReal.inv_zero, ENNReal.coe_ne_top, mul_top, Ne, not_false_iff,
mul_zero, ENNReal.coe_zero, ENNReal.inv_eq_zero]
rw [← ENNReal.coe_mul, ← ENNReal.coe_inv, ← ENNReal.coe_inv h'a, ← ENNReal.coe_inv h'b, ←
ENNReal.coe_mul, mul_inv_rev, mul_comm]
simp [h'a, h'b]
protected theorem inv_div {a b : ℝ≥0∞} (htop : b ≠ ∞ ∨ a ≠ ∞) (hzero : b ≠ 0 ∨ a ≠ 0) :
(a / b)⁻¹ = b / a := by
rw [← ENNReal.inv_ne_zero] at htop
rw [← ENNReal.inv_ne_top] at hzero
rw [ENNReal.div_eq_inv_mul, ENNReal.div_eq_inv_mul, ENNReal.mul_inv htop hzero, mul_comm, inv_inv]
protected theorem mul_div_mul_left (a b : ℝ≥0∞) (hc : c ≠ 0) (hc' : c ≠ ⊤) :
c * a / (c * b) = a / b := by
rw [div_eq_mul_inv, div_eq_mul_inv, ENNReal.mul_inv (Or.inl hc) (Or.inl hc'), mul_mul_mul_comm,
ENNReal.mul_inv_cancel hc hc', one_mul]
protected theorem mul_div_mul_right (a b : ℝ≥0∞) (hc : c ≠ 0) (hc' : c ≠ ⊤) :
a * c / (b * c) = a / b := by
rw [div_eq_mul_inv, div_eq_mul_inv, ENNReal.mul_inv (Or.inr hc') (Or.inr hc), mul_mul_mul_comm,
ENNReal.mul_inv_cancel hc hc', mul_one]
protected theorem sub_div (h : 0 < b → b < a → c ≠ 0) : (a - b) / c = a / c - b / c := by
simp_rw [div_eq_mul_inv]
exact ENNReal.sub_mul (by simpa using h)
@[simp]
protected theorem inv_pos : 0 < a⁻¹ ↔ a ≠ ∞ :=
pos_iff_ne_zero.trans ENNReal.inv_ne_zero
theorem inv_strictAnti : StrictAnti (Inv.inv : ℝ≥0∞ → ℝ≥0∞) := by
intro a b h
lift a to ℝ≥0 using h.ne_top
induction b; · simp
rw [coe_lt_coe] at h
rcases eq_or_ne a 0 with (rfl | ha); · simp [h]
rw [← coe_inv h.ne_bot, ← coe_inv ha, coe_lt_coe]
exact NNReal.inv_lt_inv ha h
@[simp]
protected theorem inv_lt_inv : a⁻¹ < b⁻¹ ↔ b < a :=
inv_strictAnti.lt_iff_lt
theorem inv_lt_iff_inv_lt : a⁻¹ < b ↔ b⁻¹ < a := by
simpa only [inv_inv] using @ENNReal.inv_lt_inv a b⁻¹
theorem lt_inv_iff_lt_inv : a < b⁻¹ ↔ b < a⁻¹ := by
simpa only [inv_inv] using @ENNReal.inv_lt_inv a⁻¹ b
@[simp]
protected theorem inv_le_inv : a⁻¹ ≤ b⁻¹ ↔ b ≤ a :=
inv_strictAnti.le_iff_le
theorem inv_le_iff_inv_le : a⁻¹ ≤ b ↔ b⁻¹ ≤ a := by
simpa only [inv_inv] using @ENNReal.inv_le_inv a b⁻¹
theorem le_inv_iff_le_inv : a ≤ b⁻¹ ↔ b ≤ a⁻¹ := by
simpa only [inv_inv] using @ENNReal.inv_le_inv a⁻¹ b
@[gcongr] protected theorem inv_le_inv' (h : a ≤ b) : b⁻¹ ≤ a⁻¹ :=
ENNReal.inv_strictAnti.antitone h
@[gcongr] protected theorem inv_lt_inv' (h : a < b) : b⁻¹ < a⁻¹ := ENNReal.inv_strictAnti h
@[simp]
protected theorem inv_le_one : a⁻¹ ≤ 1 ↔ 1 ≤ a := by rw [inv_le_iff_inv_le, inv_one]
protected theorem one_le_inv : 1 ≤ a⁻¹ ↔ a ≤ 1 := by rw [le_inv_iff_le_inv, inv_one]
@[simp]
protected theorem inv_lt_one : a⁻¹ < 1 ↔ 1 < a := by rw [inv_lt_iff_inv_lt, inv_one]
@[simp]
protected theorem one_lt_inv : 1 < a⁻¹ ↔ a < 1 := by rw [lt_inv_iff_lt_inv, inv_one]
/-- The inverse map `fun x ↦ x⁻¹` is an order isomorphism between `ℝ≥0∞` and its `OrderDual` -/
@[simps! apply]
def _root_.OrderIso.invENNReal : ℝ≥0∞ ≃o ℝ≥0∞ᵒᵈ where
map_rel_iff' := ENNReal.inv_le_inv
toEquiv := (Equiv.inv ℝ≥0∞).trans OrderDual.toDual
@[simp]
theorem _root_.OrderIso.invENNReal_symm_apply (a : ℝ≥0∞ᵒᵈ) :
OrderIso.invENNReal.symm a = (OrderDual.ofDual a)⁻¹ :=
rfl
@[simp] theorem div_top : a / ∞ = 0 := by rw [div_eq_mul_inv, inv_top, mul_zero]
theorem top_div : ∞ / a = if a = ∞ then 0 else ∞ := by simp [div_eq_mul_inv, top_mul']
theorem top_div_of_ne_top (h : a ≠ ∞) : ∞ / a = ∞ := by simp [top_div, h]
@[simp] theorem top_div_coe : ∞ / p = ∞ := top_div_of_ne_top coe_ne_top
theorem top_div_of_lt_top (h : a < ∞) : ∞ / a = ∞ := top_div_of_ne_top h.ne
@[simp] protected theorem zero_div : 0 / a = 0 := zero_mul a⁻¹
theorem div_eq_top : a / b = ∞ ↔ a ≠ 0 ∧ b = 0 ∨ a = ∞ ∧ b ≠ ∞ := by
simp [div_eq_mul_inv, ENNReal.mul_eq_top]
protected theorem le_div_iff_mul_le (h0 : b ≠ 0 ∨ c ≠ 0) (ht : b ≠ ∞ ∨ c ≠ ∞) :
a ≤ c / b ↔ a * b ≤ c := by
induction' b with b
· lift c to ℝ≥0 using ht.neg_resolve_left rfl
rw [div_top, nonpos_iff_eq_zero]
rcases eq_or_ne a 0 with (rfl | ha) <;> simp [*]
rcases eq_or_ne b 0 with (rfl | hb)
· have hc : c ≠ 0 := h0.neg_resolve_left rfl
simp [div_zero hc]
· rw [← coe_ne_zero] at hb
rw [← ENNReal.mul_le_mul_right hb coe_ne_top, ENNReal.div_mul_cancel hb coe_ne_top]
protected theorem div_le_iff_le_mul (hb0 : b ≠ 0 ∨ c ≠ ∞) (hbt : b ≠ ∞ ∨ c ≠ 0) :
a / b ≤ c ↔ a ≤ c * b := by
suffices a * b⁻¹ ≤ c ↔ a ≤ c / b⁻¹ by simpa [div_eq_mul_inv]
refine (ENNReal.le_div_iff_mul_le ?_ ?_).symm <;> simpa
protected theorem lt_div_iff_mul_lt (hb0 : b ≠ 0 ∨ c ≠ ∞) (hbt : b ≠ ∞ ∨ c ≠ 0) :
c < a / b ↔ c * b < a :=
lt_iff_lt_of_le_iff_le (ENNReal.div_le_iff_le_mul hb0 hbt)
theorem div_le_of_le_mul (h : a ≤ b * c) : a / c ≤ b := by
by_cases h0 : c = 0
· have : a = 0 := by simpa [h0] using h
simp [*]
by_cases hinf : c = ∞; · simp [hinf]
exact (ENNReal.div_le_iff_le_mul (Or.inl h0) (Or.inl hinf)).2 h
theorem div_le_of_le_mul' (h : a ≤ b * c) : a / b ≤ c :=
div_le_of_le_mul <| mul_comm b c ▸ h
@[simp] protected theorem div_self_le_one : a / a ≤ 1 := div_le_of_le_mul <| by rw [one_mul]
@[simp] protected lemma mul_inv_le_one (a : ℝ≥0∞) : a * a⁻¹ ≤ 1 := ENNReal.div_self_le_one
@[simp] protected lemma inv_mul_le_one (a : ℝ≥0∞) : a⁻¹ * a ≤ 1 := by simp [mul_comm]
@[simp] lemma mul_inv_ne_top (a : ℝ≥0∞) : a * a⁻¹ ≠ ⊤ :=
ne_top_of_le_ne_top one_ne_top a.mul_inv_le_one
@[simp] lemma inv_mul_ne_top (a : ℝ≥0∞) : a⁻¹ * a ≠ ⊤ := by simp [mul_comm]
theorem mul_le_of_le_div (h : a ≤ b / c) : a * c ≤ b := by
rw [← inv_inv c]
exact div_le_of_le_mul h
theorem mul_le_of_le_div' (h : a ≤ b / c) : c * a ≤ b :=
mul_comm a c ▸ mul_le_of_le_div h
protected theorem div_lt_iff (h0 : b ≠ 0 ∨ c ≠ 0) (ht : b ≠ ∞ ∨ c ≠ ∞) : c / b < a ↔ c < a * b :=
lt_iff_lt_of_le_iff_le <| ENNReal.le_div_iff_mul_le h0 ht
theorem mul_lt_of_lt_div (h : a < b / c) : a * c < b := by
contrapose! h
exact ENNReal.div_le_of_le_mul h
theorem mul_lt_of_lt_div' (h : a < b / c) : c * a < b :=
mul_comm a c ▸ mul_lt_of_lt_div h
theorem div_lt_of_lt_mul (h : a < b * c) : a / c < b :=
mul_lt_of_lt_div <| by rwa [div_eq_mul_inv, inv_inv]
| Mathlib/Data/ENNReal/Inv.lean | 398 | 402 | theorem div_lt_of_lt_mul' (h : a < b * c) : a / b < c :=
div_lt_of_lt_mul <| by rwa [mul_comm]
theorem inv_le_iff_le_mul (h₁ : b = ∞ → a ≠ 0) (h₂ : a = ∞ → b ≠ 0) : a⁻¹ ≤ b ↔ 1 ≤ a * b := by | rw [← one_div, ENNReal.div_le_iff_le_mul, mul_comm] |
/-
Copyright (c) 2022 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.MeasureTheory.Function.StronglyMeasurable.Basic
/-!
# Egorov theorem
This file contains the Egorov theorem which states that an almost everywhere convergent
sequence on a finite measure space converges uniformly except on an arbitrarily small set.
This theorem is useful for the Vitali convergence theorem as well as theorems regarding
convergence in measure.
## Main results
* `MeasureTheory.tendstoUniformlyOn_of_ae_tendsto`: Egorov's theorem which shows that a sequence of
almost everywhere convergent functions converges uniformly except on an arbitrarily small set.
-/
noncomputable section
open MeasureTheory NNReal ENNReal Topology
namespace MeasureTheory
open Set Filter TopologicalSpace
variable {α β ι : Type*} {m : MeasurableSpace α} [MetricSpace β] {μ : Measure α}
namespace Egorov
/-- Given a sequence of functions `f` and a function `g`, `notConvergentSeq f g n j` is the
set of elements such that `f k x` and `g x` are separated by at least `1 / (n + 1)` for some
`k ≥ j`.
This definition is useful for Egorov's theorem. -/
def notConvergentSeq [Preorder ι] (f : ι → α → β) (g : α → β) (n : ℕ) (j : ι) : Set α :=
⋃ (k) (_ : j ≤ k), { x | 1 / (n + 1 : ℝ) < dist (f k x) (g x) }
variable {n : ℕ} {j : ι} {s : Set α} {ε : ℝ} {f : ι → α → β} {g : α → β}
theorem mem_notConvergentSeq_iff [Preorder ι] {x : α} :
x ∈ notConvergentSeq f g n j ↔ ∃ k ≥ j, 1 / (n + 1 : ℝ) < dist (f k x) (g x) := by
simp_rw [notConvergentSeq, Set.mem_iUnion, exists_prop, mem_setOf]
theorem notConvergentSeq_antitone [Preorder ι] : Antitone (notConvergentSeq f g n) :=
fun _ _ hjk => Set.iUnion₂_mono' fun l hl => ⟨l, le_trans hjk hl, Set.Subset.rfl⟩
theorem measure_inter_notConvergentSeq_eq_zero [SemilatticeSup ι] [Nonempty ι]
(hfg : ∀ᵐ x ∂μ, x ∈ s → Tendsto (fun n => f n x) atTop (𝓝 (g x))) (n : ℕ) :
μ (s ∩ ⋂ j, notConvergentSeq f g n j) = 0 := by
simp_rw [Metric.tendsto_atTop, ae_iff] at hfg
rw [← nonpos_iff_eq_zero, ← hfg]
refine measure_mono fun x => ?_
simp only [Set.mem_inter_iff, Set.mem_iInter, mem_notConvergentSeq_iff]
push_neg
rintro ⟨hmem, hx⟩
refine ⟨hmem, 1 / (n + 1 : ℝ), Nat.one_div_pos_of_nat, fun N => ?_⟩
obtain ⟨n, hn₁, hn₂⟩ := hx N
exact ⟨n, hn₁, hn₂.le⟩
theorem notConvergentSeq_measurableSet [Preorder ι] [Countable ι]
(hf : ∀ n, StronglyMeasurable[m] (f n)) (hg : StronglyMeasurable g) :
MeasurableSet (notConvergentSeq f g n j) :=
MeasurableSet.iUnion fun k =>
MeasurableSet.iUnion fun _ =>
StronglyMeasurable.measurableSet_lt stronglyMeasurable_const <| (hf k).dist hg
theorem measure_notConvergentSeq_tendsto_zero [SemilatticeSup ι] [Countable ι]
(hf : ∀ n, StronglyMeasurable (f n)) (hg : StronglyMeasurable g) (hsm : MeasurableSet s)
(hs : μ s ≠ ∞) (hfg : ∀ᵐ x ∂μ, x ∈ s → Tendsto (fun n => f n x) atTop (𝓝 (g x))) (n : ℕ) :
Tendsto (fun j => μ (s ∩ notConvergentSeq f g n j)) atTop (𝓝 0) := by
rcases isEmpty_or_nonempty ι with h | h
· have : (fun j => μ (s ∩ notConvergentSeq f g n j)) = fun j => 0 := by
simp only [eq_iff_true_of_subsingleton]
rw [this]
exact tendsto_const_nhds
rw [← measure_inter_notConvergentSeq_eq_zero hfg n, Set.inter_iInter]
refine tendsto_measure_iInter_atTop
(fun n ↦ (hsm.inter <| notConvergentSeq_measurableSet hf hg).nullMeasurableSet)
(fun k l hkl => Set.inter_subset_inter_right _ <| notConvergentSeq_antitone hkl)
⟨h.some, ne_top_of_le_ne_top hs (measure_mono Set.inter_subset_left)⟩
variable [SemilatticeSup ι] [Nonempty ι] [Countable ι]
theorem exists_notConvergentSeq_lt (hε : 0 < ε) (hf : ∀ n, StronglyMeasurable (f n))
(hg : StronglyMeasurable g) (hsm : MeasurableSet s) (hs : μ s ≠ ∞)
(hfg : ∀ᵐ x ∂μ, x ∈ s → Tendsto (fun n => f n x) atTop (𝓝 (g x))) (n : ℕ) :
∃ j : ι, μ (s ∩ notConvergentSeq f g n j) ≤ ENNReal.ofReal (ε * 2⁻¹ ^ n) := by
have ⟨N, hN⟩ := (ENNReal.tendsto_atTop ENNReal.zero_ne_top).1
(measure_notConvergentSeq_tendsto_zero hf hg hsm hs hfg n) (ENNReal.ofReal (ε * 2⁻¹ ^ n)) (by
rw [gt_iff_lt, ENNReal.ofReal_pos]
exact mul_pos hε (pow_pos (by norm_num) n))
rw [zero_add] at hN
exact ⟨N, (hN N le_rfl).2⟩
/-- Given some `ε > 0`, `notConvergentSeqLTIndex` provides the index such that
`notConvergentSeq` (intersected with a set of finite measure) has measure less than
`ε * 2⁻¹ ^ n`.
This definition is useful for Egorov's theorem. -/
def notConvergentSeqLTIndex (hε : 0 < ε) (hf : ∀ n, StronglyMeasurable (f n))
(hg : StronglyMeasurable g) (hsm : MeasurableSet s) (hs : μ s ≠ ∞)
(hfg : ∀ᵐ x ∂μ, x ∈ s → Tendsto (fun n => f n x) atTop (𝓝 (g x))) (n : ℕ) : ι :=
Classical.choose <| exists_notConvergentSeq_lt hε hf hg hsm hs hfg n
theorem notConvergentSeqLTIndex_spec (hε : 0 < ε) (hf : ∀ n, StronglyMeasurable (f n))
(hg : StronglyMeasurable g) (hsm : MeasurableSet s) (hs : μ s ≠ ∞)
(hfg : ∀ᵐ x ∂μ, x ∈ s → Tendsto (fun n => f n x) atTop (𝓝 (g x))) (n : ℕ) :
μ (s ∩ notConvergentSeq f g n (notConvergentSeqLTIndex hε hf hg hsm hs hfg n)) ≤
ENNReal.ofReal (ε * 2⁻¹ ^ n) :=
Classical.choose_spec <| exists_notConvergentSeq_lt hε hf hg hsm hs hfg n
/-- Given some `ε > 0`, `iUnionNotConvergentSeq` is the union of `notConvergentSeq` with
specific indices such that `iUnionNotConvergentSeq` has measure less equal than `ε`.
This definition is useful for Egorov's theorem. -/
def iUnionNotConvergentSeq (hε : 0 < ε) (hf : ∀ n, StronglyMeasurable (f n))
(hg : StronglyMeasurable g) (hsm : MeasurableSet s) (hs : μ s ≠ ∞)
(hfg : ∀ᵐ x ∂μ, x ∈ s → Tendsto (fun n => f n x) atTop (𝓝 (g x))) : Set α :=
⋃ n, s ∩ notConvergentSeq f g n (notConvergentSeqLTIndex (half_pos hε) hf hg hsm hs hfg n)
theorem iUnionNotConvergentSeq_measurableSet (hε : 0 < ε) (hf : ∀ n, StronglyMeasurable (f n))
(hg : StronglyMeasurable g) (hsm : MeasurableSet s) (hs : μ s ≠ ∞)
(hfg : ∀ᵐ x ∂μ, x ∈ s → Tendsto (fun n => f n x) atTop (𝓝 (g x))) :
MeasurableSet <| iUnionNotConvergentSeq hε hf hg hsm hs hfg :=
MeasurableSet.iUnion fun _ => hsm.inter <| notConvergentSeq_measurableSet hf hg
theorem measure_iUnionNotConvergentSeq (hε : 0 < ε) (hf : ∀ n, StronglyMeasurable (f n))
(hg : StronglyMeasurable g) (hsm : MeasurableSet s) (hs : μ s ≠ ∞)
(hfg : ∀ᵐ x ∂μ, x ∈ s → Tendsto (fun n => f n x) atTop (𝓝 (g x))) :
μ (iUnionNotConvergentSeq hε hf hg hsm hs hfg) ≤ ENNReal.ofReal ε := by
refine le_trans (measure_iUnion_le _) (le_trans
(ENNReal.tsum_le_tsum <| notConvergentSeqLTIndex_spec (half_pos hε) hf hg hsm hs hfg) ?_)
simp_rw [ENNReal.ofReal_mul (half_pos hε).le]
rw [ENNReal.tsum_mul_left, ← ENNReal.ofReal_tsum_of_nonneg, inv_eq_one_div, tsum_geometric_two,
← ENNReal.ofReal_mul (half_pos hε).le, div_mul_cancel₀ ε two_ne_zero]
· intro n; positivity
· rw [inv_eq_one_div]
exact summable_geometric_two
| Mathlib/MeasureTheory/Function/Egorov.lean | 146 | 157 | theorem iUnionNotConvergentSeq_subset (hε : 0 < ε) (hf : ∀ n, StronglyMeasurable (f n))
(hg : StronglyMeasurable g) (hsm : MeasurableSet s) (hs : μ s ≠ ∞)
(hfg : ∀ᵐ x ∂μ, x ∈ s → Tendsto (fun n => f n x) atTop (𝓝 (g x))) :
iUnionNotConvergentSeq hε hf hg hsm hs hfg ⊆ s := by | rw [iUnionNotConvergentSeq, ← Set.inter_iUnion]
exact Set.inter_subset_left
theorem tendstoUniformlyOn_diff_iUnionNotConvergentSeq (hε : 0 < ε)
(hf : ∀ n, StronglyMeasurable (f n)) (hg : StronglyMeasurable g) (hsm : MeasurableSet s)
(hs : μ s ≠ ∞) (hfg : ∀ᵐ x ∂μ, x ∈ s → Tendsto (fun n => f n x) atTop (𝓝 (g x))) :
TendstoUniformlyOn f g atTop (s \ Egorov.iUnionNotConvergentSeq hε hf hg hsm hs hfg) := by
rw [Metric.tendstoUniformlyOn_iff] |
/-
Copyright (c) 2018 Patrick Massot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Patrick Massot, Johannes Hölzl, Yaël Dillies
-/
import Mathlib.Analysis.Normed.Group.Continuity
import Mathlib.Topology.Algebra.IsUniformGroup.Basic
import Mathlib.Topology.MetricSpace.Algebra
import Mathlib.Topology.MetricSpace.IsometricSMul
/-!
# Normed groups are uniform groups
This file proves lipschitzness of normed group operations and shows that normed groups are uniform
groups.
-/
variable {𝓕 E F : Type*}
open Filter Function Metric Bornology
open scoped ENNReal NNReal Uniformity Pointwise Topology
section SeminormedGroup
variable [SeminormedGroup E] [SeminormedGroup F] {s : Set E} {a b : E} {r : ℝ}
@[to_additive]
instance NormedGroup.to_isIsometricSMul_right : IsIsometricSMul Eᵐᵒᵖ E :=
⟨fun a => Isometry.of_dist_eq fun b c => by simp [dist_eq_norm_div]⟩
@[to_additive]
theorem Isometry.norm_map_of_map_one {f : E → F} (hi : Isometry f) (h₁ : f 1 = 1) (x : E) :
‖f x‖ = ‖x‖ := by rw [← dist_one_right, ← h₁, hi.dist_eq, dist_one_right]
@[to_additive (attr := simp)]
theorem dist_mul_self_right (a b : E) : dist b (a * b) = ‖a‖ := by
rw [← dist_one_left, ← dist_mul_right 1 a b, one_mul]
@[to_additive (attr := simp)]
theorem dist_mul_self_left (a b : E) : dist (a * b) b = ‖a‖ := by
rw [dist_comm, dist_mul_self_right]
@[to_additive (attr := simp)]
theorem dist_div_eq_dist_mul_left (a b c : E) : dist (a / b) c = dist a (c * b) := by
rw [← dist_mul_right _ _ b, div_mul_cancel]
@[to_additive (attr := simp)]
| Mathlib/Analysis/Normed/Group/Uniform.lean | 47 | 48 | theorem dist_div_eq_dist_mul_right (a b c : E) : dist a (b / c) = dist (a * c) b := by | rw [← dist_mul_right _ _ c, div_mul_cancel] |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jeremy Avigad
-/
import Mathlib.Algebra.Group.Basic
import Mathlib.Algebra.Notation.Pi
import Mathlib.Data.Set.Lattice
import Mathlib.Order.Filter.Defs
/-!
# Theory of filters on sets
A *filter* on a type `α` is a collection of sets of `α` which contains the whole `α`,
is upwards-closed, and is stable under intersection. They are mostly used to
abstract two related kinds of ideas:
* *limits*, including finite or infinite limits of sequences, finite or infinite limits of functions
at a point or at infinity, etc...
* *things happening eventually*, including things happening for large enough `n : ℕ`, or near enough
a point `x`, or for close enough pairs of points, or things happening almost everywhere in the
sense of measure theory. Dually, filters can also express the idea of *things happening often*:
for arbitrarily large `n`, or at a point in any neighborhood of given a point etc...
## Main definitions
In this file, we endow `Filter α` it with a complete lattice structure.
This structure is lifted from the lattice structure on `Set (Set X)` using the Galois
insertion which maps a filter to its elements in one direction, and an arbitrary set of sets to
the smallest filter containing it in the other direction.
We also prove `Filter` is a monadic functor, with a push-forward operation
`Filter.map` and a pull-back operation `Filter.comap` that form a Galois connections for the
order on filters.
The examples of filters appearing in the description of the two motivating ideas are:
* `(Filter.atTop : Filter ℕ)` : made of sets of `ℕ` containing `{n | n ≥ N}` for some `N`
* `𝓝 x` : made of neighborhoods of `x` in a topological space (defined in topology.basic)
* `𝓤 X` : made of entourages of a uniform space (those space are generalizations of metric spaces
defined in `Mathlib/Topology/UniformSpace/Basic.lean`)
* `MeasureTheory.ae` : made of sets whose complement has zero measure with respect to `μ`
(defined in `Mathlib/MeasureTheory/OuterMeasure/AE`)
The predicate "happening eventually" is `Filter.Eventually`, and "happening often" is
`Filter.Frequently`, whose definitions are immediate after `Filter` is defined (but they come
rather late in this file in order to immediately relate them to the lattice structure).
## Notations
* `∀ᶠ x in f, p x` : `f.Eventually p`;
* `∃ᶠ x in f, p x` : `f.Frequently p`;
* `f =ᶠ[l] g` : `∀ᶠ x in l, f x = g x`;
* `f ≤ᶠ[l] g` : `∀ᶠ x in l, f x ≤ g x`;
* `𝓟 s` : `Filter.Principal s`, localized in `Filter`.
## References
* [N. Bourbaki, *General Topology*][bourbaki1966]
Important note: Bourbaki requires that a filter on `X` cannot contain all sets of `X`, which
we do *not* require. This gives `Filter X` better formal properties, in particular a bottom element
`⊥` for its lattice structure, at the cost of including the assumption
`[NeBot f]` in a number of lemmas and definitions.
-/
assert_not_exists OrderedSemiring Fintype
open Function Set Order
open scoped symmDiff
universe u v w x y
namespace Filter
variable {α : Type u} {f g : Filter α} {s t : Set α}
instance inhabitedMem : Inhabited { s : Set α // s ∈ f } :=
⟨⟨univ, f.univ_sets⟩⟩
theorem filter_eq_iff : f = g ↔ f.sets = g.sets :=
⟨congr_arg _, filter_eq⟩
@[simp] theorem sets_subset_sets : f.sets ⊆ g.sets ↔ g ≤ f := .rfl
@[simp] theorem sets_ssubset_sets : f.sets ⊂ g.sets ↔ g < f := .rfl
/-- An extensionality lemma that is useful for filters with good lemmas about `sᶜ ∈ f` (e.g.,
`Filter.comap`, `Filter.coprod`, `Filter.Coprod`, `Filter.cofinite`). -/
protected theorem coext (h : ∀ s, sᶜ ∈ f ↔ sᶜ ∈ g) : f = g :=
Filter.ext <| compl_surjective.forall.2 h
instance : Trans (· ⊇ ·) ((· ∈ ·) : Set α → Filter α → Prop) (· ∈ ·) where
trans h₁ h₂ := mem_of_superset h₂ h₁
instance : Trans Membership.mem (· ⊆ ·) (Membership.mem : Filter α → Set α → Prop) where
trans h₁ h₂ := mem_of_superset h₁ h₂
@[simp]
theorem inter_mem_iff {s t : Set α} : s ∩ t ∈ f ↔ s ∈ f ∧ t ∈ f :=
⟨fun h => ⟨mem_of_superset h inter_subset_left, mem_of_superset h inter_subset_right⟩,
and_imp.2 inter_mem⟩
theorem diff_mem {s t : Set α} (hs : s ∈ f) (ht : tᶜ ∈ f) : s \ t ∈ f :=
inter_mem hs ht
theorem congr_sets (h : { x | x ∈ s ↔ x ∈ t } ∈ f) : s ∈ f ↔ t ∈ f :=
⟨fun hs => mp_mem hs (mem_of_superset h fun _ => Iff.mp), fun hs =>
mp_mem hs (mem_of_superset h fun _ => Iff.mpr)⟩
lemma copy_eq {S} (hmem : ∀ s, s ∈ S ↔ s ∈ f) : f.copy S hmem = f := Filter.ext hmem
/-- Weaker version of `Filter.biInter_mem` that assumes `Subsingleton β` rather than `Finite β`. -/
theorem biInter_mem' {β : Type v} {s : β → Set α} {is : Set β} (hf : is.Subsingleton) :
(⋂ i ∈ is, s i) ∈ f ↔ ∀ i ∈ is, s i ∈ f := by
apply Subsingleton.induction_on hf <;> simp
/-- Weaker version of `Filter.iInter_mem` that assumes `Subsingleton β` rather than `Finite β`. -/
theorem iInter_mem' {β : Sort v} {s : β → Set α} [Subsingleton β] :
(⋂ i, s i) ∈ f ↔ ∀ i, s i ∈ f := by
rw [← sInter_range, sInter_eq_biInter, biInter_mem' (subsingleton_range s), forall_mem_range]
theorem exists_mem_subset_iff : (∃ t ∈ f, t ⊆ s) ↔ s ∈ f :=
⟨fun ⟨_, ht, ts⟩ => mem_of_superset ht ts, fun hs => ⟨s, hs, Subset.rfl⟩⟩
theorem monotone_mem {f : Filter α} : Monotone fun s => s ∈ f := fun _ _ hst h =>
mem_of_superset h hst
theorem exists_mem_and_iff {P : Set α → Prop} {Q : Set α → Prop} (hP : Antitone P)
(hQ : Antitone Q) : ((∃ u ∈ f, P u) ∧ ∃ u ∈ f, Q u) ↔ ∃ u ∈ f, P u ∧ Q u := by
constructor
· rintro ⟨⟨u, huf, hPu⟩, v, hvf, hQv⟩
exact
⟨u ∩ v, inter_mem huf hvf, hP inter_subset_left hPu, hQ inter_subset_right hQv⟩
· rintro ⟨u, huf, hPu, hQu⟩
exact ⟨⟨u, huf, hPu⟩, u, huf, hQu⟩
theorem forall_in_swap {β : Type*} {p : Set α → β → Prop} :
(∀ a ∈ f, ∀ (b), p a b) ↔ ∀ (b), ∀ a ∈ f, p a b :=
Set.forall_in_swap
end Filter
namespace Filter
variable {α : Type u} {β : Type v} {γ : Type w} {δ : Type*} {ι : Sort x}
theorem mem_principal_self (s : Set α) : s ∈ 𝓟 s := Subset.rfl
section Lattice
variable {f g : Filter α} {s t : Set α}
protected theorem not_le : ¬f ≤ g ↔ ∃ s ∈ g, s ∉ f := by simp_rw [le_def, not_forall, exists_prop]
/-- `GenerateSets g s`: `s` is in the filter closure of `g`. -/
inductive GenerateSets (g : Set (Set α)) : Set α → Prop
| basic {s : Set α} : s ∈ g → GenerateSets g s
| univ : GenerateSets g univ
| superset {s t : Set α} : GenerateSets g s → s ⊆ t → GenerateSets g t
| inter {s t : Set α} : GenerateSets g s → GenerateSets g t → GenerateSets g (s ∩ t)
/-- `generate g` is the largest filter containing the sets `g`. -/
def generate (g : Set (Set α)) : Filter α where
sets := {s | GenerateSets g s}
univ_sets := GenerateSets.univ
sets_of_superset := GenerateSets.superset
inter_sets := GenerateSets.inter
lemma mem_generate_of_mem {s : Set <| Set α} {U : Set α} (h : U ∈ s) :
U ∈ generate s := GenerateSets.basic h
theorem le_generate_iff {s : Set (Set α)} {f : Filter α} : f ≤ generate s ↔ s ⊆ f.sets :=
Iff.intro (fun h _ hu => h <| GenerateSets.basic <| hu) fun h _ hu =>
hu.recOn (fun h' => h h') univ_mem (fun _ hxy hx => mem_of_superset hx hxy) fun _ _ hx hy =>
inter_mem hx hy
@[simp] lemma generate_singleton (s : Set α) : generate {s} = 𝓟 s :=
le_antisymm (fun _t ht ↦ mem_of_superset (mem_generate_of_mem <| mem_singleton _) ht) <|
le_generate_iff.2 <| singleton_subset_iff.2 Subset.rfl
/-- `mkOfClosure s hs` constructs a filter on `α` whose elements set is exactly
`s : Set (Set α)`, provided one gives the assumption `hs : (generate s).sets = s`. -/
protected def mkOfClosure (s : Set (Set α)) (hs : (generate s).sets = s) : Filter α where
sets := s
univ_sets := hs ▸ univ_mem
sets_of_superset := hs ▸ mem_of_superset
inter_sets := hs ▸ inter_mem
theorem mkOfClosure_sets {s : Set (Set α)} {hs : (generate s).sets = s} :
Filter.mkOfClosure s hs = generate s :=
Filter.ext fun u =>
show u ∈ (Filter.mkOfClosure s hs).sets ↔ u ∈ (generate s).sets from hs.symm ▸ Iff.rfl
/-- Galois insertion from sets of sets into filters. -/
def giGenerate (α : Type*) :
@GaloisInsertion (Set (Set α)) (Filter α)ᵒᵈ _ _ Filter.generate Filter.sets where
gc _ _ := le_generate_iff
le_l_u _ _ h := GenerateSets.basic h
choice s hs := Filter.mkOfClosure s (le_antisymm hs <| le_generate_iff.1 <| le_rfl)
choice_eq _ _ := mkOfClosure_sets
theorem mem_inf_iff {f g : Filter α} {s : Set α} : s ∈ f ⊓ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, s = t₁ ∩ t₂ :=
Iff.rfl
theorem mem_inf_of_left {f g : Filter α} {s : Set α} (h : s ∈ f) : s ∈ f ⊓ g :=
⟨s, h, univ, univ_mem, (inter_univ s).symm⟩
theorem mem_inf_of_right {f g : Filter α} {s : Set α} (h : s ∈ g) : s ∈ f ⊓ g :=
⟨univ, univ_mem, s, h, (univ_inter s).symm⟩
theorem inter_mem_inf {α : Type u} {f g : Filter α} {s t : Set α} (hs : s ∈ f) (ht : t ∈ g) :
s ∩ t ∈ f ⊓ g :=
⟨s, hs, t, ht, rfl⟩
theorem mem_inf_of_inter {f g : Filter α} {s t u : Set α} (hs : s ∈ f) (ht : t ∈ g)
(h : s ∩ t ⊆ u) : u ∈ f ⊓ g :=
mem_of_superset (inter_mem_inf hs ht) h
theorem mem_inf_iff_superset {f g : Filter α} {s : Set α} :
s ∈ f ⊓ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, t₁ ∩ t₂ ⊆ s :=
⟨fun ⟨t₁, h₁, t₂, h₂, Eq⟩ => ⟨t₁, h₁, t₂, h₂, Eq ▸ Subset.rfl⟩, fun ⟨_, h₁, _, h₂, sub⟩ =>
mem_inf_of_inter h₁ h₂ sub⟩
section CompleteLattice
/-- Complete lattice structure on `Filter α`. -/
instance instCompleteLatticeFilter : CompleteLattice (Filter α) where
inf a b := min a b
sup a b := max a b
le_sup_left _ _ _ h := h.1
le_sup_right _ _ _ h := h.2
sup_le _ _ _ h₁ h₂ _ h := ⟨h₁ h, h₂ h⟩
inf_le_left _ _ _ := mem_inf_of_left
inf_le_right _ _ _ := mem_inf_of_right
le_inf := fun _ _ _ h₁ h₂ _s ⟨_a, ha, _b, hb, hs⟩ => hs.symm ▸ inter_mem (h₁ ha) (h₂ hb)
le_sSup _ _ h₁ _ h₂ := h₂ h₁
sSup_le _ _ h₁ _ h₂ _ h₃ := h₁ _ h₃ h₂
sInf_le _ _ h₁ _ h₂ := by rw [← Filter.sSup_lowerBounds]; exact fun _ h₃ ↦ h₃ h₁ h₂
le_sInf _ _ h₁ _ h₂ := by rw [← Filter.sSup_lowerBounds] at h₂; exact h₂ h₁
le_top _ _ := univ_mem'
bot_le _ _ _ := trivial
instance : Inhabited (Filter α) := ⟨⊥⟩
end CompleteLattice
theorem NeBot.ne {f : Filter α} (hf : NeBot f) : f ≠ ⊥ := hf.ne'
@[simp] theorem not_neBot {f : Filter α} : ¬f.NeBot ↔ f = ⊥ := neBot_iff.not_left
theorem NeBot.mono {f g : Filter α} (hf : NeBot f) (hg : f ≤ g) : NeBot g :=
⟨ne_bot_of_le_ne_bot hf.1 hg⟩
theorem neBot_of_le {f g : Filter α} [hf : NeBot f] (hg : f ≤ g) : NeBot g :=
hf.mono hg
@[simp] theorem sup_neBot {f g : Filter α} : NeBot (f ⊔ g) ↔ NeBot f ∨ NeBot g := by
simp only [neBot_iff, not_and_or, Ne, sup_eq_bot_iff]
theorem not_disjoint_self_iff : ¬Disjoint f f ↔ f.NeBot := by rw [disjoint_self, neBot_iff]
theorem bot_sets_eq : (⊥ : Filter α).sets = univ := rfl
/-- Either `f = ⊥` or `Filter.NeBot f`. This is a version of `eq_or_ne` that uses `Filter.NeBot`
as the second alternative, to be used as an instance. -/
theorem eq_or_neBot (f : Filter α) : f = ⊥ ∨ NeBot f := (eq_or_ne f ⊥).imp_right NeBot.mk
theorem sup_sets_eq {f g : Filter α} : (f ⊔ g).sets = f.sets ∩ g.sets :=
(giGenerate α).gc.u_inf
theorem sSup_sets_eq {s : Set (Filter α)} : (sSup s).sets = ⋂ f ∈ s, (f : Filter α).sets :=
(giGenerate α).gc.u_sInf
theorem iSup_sets_eq {f : ι → Filter α} : (iSup f).sets = ⋂ i, (f i).sets :=
(giGenerate α).gc.u_iInf
theorem generate_empty : Filter.generate ∅ = (⊤ : Filter α) :=
(giGenerate α).gc.l_bot
theorem generate_univ : Filter.generate univ = (⊥ : Filter α) :=
bot_unique fun _ _ => GenerateSets.basic (mem_univ _)
theorem generate_union {s t : Set (Set α)} :
Filter.generate (s ∪ t) = Filter.generate s ⊓ Filter.generate t :=
(giGenerate α).gc.l_sup
theorem generate_iUnion {s : ι → Set (Set α)} :
Filter.generate (⋃ i, s i) = ⨅ i, Filter.generate (s i) :=
(giGenerate α).gc.l_iSup
@[simp]
theorem mem_sup {f g : Filter α} {s : Set α} : s ∈ f ⊔ g ↔ s ∈ f ∧ s ∈ g :=
Iff.rfl
theorem union_mem_sup {f g : Filter α} {s t : Set α} (hs : s ∈ f) (ht : t ∈ g) : s ∪ t ∈ f ⊔ g :=
⟨mem_of_superset hs subset_union_left, mem_of_superset ht subset_union_right⟩
@[simp]
theorem mem_iSup {x : Set α} {f : ι → Filter α} : x ∈ iSup f ↔ ∀ i, x ∈ f i := by
simp only [← Filter.mem_sets, iSup_sets_eq, mem_iInter]
@[simp]
theorem iSup_neBot {f : ι → Filter α} : (⨆ i, f i).NeBot ↔ ∃ i, (f i).NeBot := by
simp [neBot_iff]
theorem iInf_eq_generate (s : ι → Filter α) : iInf s = generate (⋃ i, (s i).sets) :=
eq_of_forall_le_iff fun _ ↦ by simp [le_generate_iff]
theorem mem_iInf_of_mem {f : ι → Filter α} (i : ι) {s} (hs : s ∈ f i) : s ∈ ⨅ i, f i :=
iInf_le f i hs
@[simp]
theorem le_principal_iff {s : Set α} {f : Filter α} : f ≤ 𝓟 s ↔ s ∈ f :=
⟨fun h => h Subset.rfl, fun hs _ ht => mem_of_superset hs ht⟩
theorem Iic_principal (s : Set α) : Iic (𝓟 s) = { l | s ∈ l } :=
Set.ext fun _ => le_principal_iff
theorem principal_mono {s t : Set α} : 𝓟 s ≤ 𝓟 t ↔ s ⊆ t := by
simp only [le_principal_iff, mem_principal]
@[gcongr] alias ⟨_, _root_.GCongr.filter_principal_mono⟩ := principal_mono
@[mono]
theorem monotone_principal : Monotone (𝓟 : Set α → Filter α) := fun _ _ => principal_mono.2
@[simp] theorem principal_eq_iff_eq {s t : Set α} : 𝓟 s = 𝓟 t ↔ s = t := by
simp only [le_antisymm_iff, le_principal_iff, mem_principal]; rfl
@[simp] theorem join_principal_eq_sSup {s : Set (Filter α)} : join (𝓟 s) = sSup s := rfl
@[simp] theorem principal_univ : 𝓟 (univ : Set α) = ⊤ :=
top_unique <| by simp only [le_principal_iff, mem_top, eq_self_iff_true]
@[simp]
theorem principal_empty : 𝓟 (∅ : Set α) = ⊥ :=
bot_unique fun _ _ => empty_subset _
theorem generate_eq_biInf (S : Set (Set α)) : generate S = ⨅ s ∈ S, 𝓟 s :=
eq_of_forall_le_iff fun f => by simp [le_generate_iff, le_principal_iff, subset_def]
/-! ### Lattice equations -/
theorem empty_mem_iff_bot {f : Filter α} : ∅ ∈ f ↔ f = ⊥ :=
⟨fun h => bot_unique fun s _ => mem_of_superset h (empty_subset s), fun h => h.symm ▸ mem_bot⟩
theorem nonempty_of_mem {f : Filter α} [hf : NeBot f] {s : Set α} (hs : s ∈ f) : s.Nonempty :=
s.eq_empty_or_nonempty.elim (fun h => absurd hs (h.symm ▸ mt empty_mem_iff_bot.mp hf.1)) id
theorem NeBot.nonempty_of_mem {f : Filter α} (hf : NeBot f) {s : Set α} (hs : s ∈ f) : s.Nonempty :=
@Filter.nonempty_of_mem α f hf s hs
@[simp]
theorem empty_not_mem (f : Filter α) [NeBot f] : ¬∅ ∈ f := fun h => (nonempty_of_mem h).ne_empty rfl
theorem nonempty_of_neBot (f : Filter α) [NeBot f] : Nonempty α :=
nonempty_of_exists <| nonempty_of_mem (univ_mem : univ ∈ f)
theorem compl_not_mem {f : Filter α} {s : Set α} [NeBot f] (h : s ∈ f) : sᶜ ∉ f := fun hsc =>
(nonempty_of_mem (inter_mem h hsc)).ne_empty <| inter_compl_self s
theorem filter_eq_bot_of_isEmpty [IsEmpty α] (f : Filter α) : f = ⊥ :=
empty_mem_iff_bot.mp <| univ_mem' isEmptyElim
protected lemma disjoint_iff {f g : Filter α} : Disjoint f g ↔ ∃ s ∈ f, ∃ t ∈ g, Disjoint s t := by
simp only [disjoint_iff, ← empty_mem_iff_bot, mem_inf_iff, inf_eq_inter, bot_eq_empty,
@eq_comm _ ∅]
theorem disjoint_of_disjoint_of_mem {f g : Filter α} {s t : Set α} (h : Disjoint s t) (hs : s ∈ f)
(ht : t ∈ g) : Disjoint f g :=
Filter.disjoint_iff.mpr ⟨s, hs, t, ht, h⟩
theorem NeBot.not_disjoint (hf : f.NeBot) (hs : s ∈ f) (ht : t ∈ f) : ¬Disjoint s t := fun h =>
not_disjoint_self_iff.2 hf <| Filter.disjoint_iff.2 ⟨s, hs, t, ht, h⟩
theorem inf_eq_bot_iff {f g : Filter α} : f ⊓ g = ⊥ ↔ ∃ U ∈ f, ∃ V ∈ g, U ∩ V = ∅ := by
simp only [← disjoint_iff, Filter.disjoint_iff, Set.disjoint_iff_inter_eq_empty]
/-- There is exactly one filter on an empty type. -/
instance unique [IsEmpty α] : Unique (Filter α) where
default := ⊥
uniq := filter_eq_bot_of_isEmpty
theorem NeBot.nonempty (f : Filter α) [hf : f.NeBot] : Nonempty α :=
not_isEmpty_iff.mp fun _ ↦ hf.ne (Subsingleton.elim _ _)
/-- There are only two filters on a `Subsingleton`: `⊥` and `⊤`. If the type is empty, then they are
equal. -/
theorem eq_top_of_neBot [Subsingleton α] (l : Filter α) [NeBot l] : l = ⊤ := by
refine top_unique fun s hs => ?_
obtain rfl : s = univ := Subsingleton.eq_univ_of_nonempty (nonempty_of_mem hs)
exact univ_mem
theorem forall_mem_nonempty_iff_neBot {f : Filter α} :
(∀ s : Set α, s ∈ f → s.Nonempty) ↔ NeBot f :=
⟨fun h => ⟨fun hf => not_nonempty_empty (h ∅ <| hf.symm ▸ mem_bot)⟩, @nonempty_of_mem _ _⟩
instance instNeBotTop [Nonempty α] : NeBot (⊤ : Filter α) :=
forall_mem_nonempty_iff_neBot.1 fun s hs => by rwa [mem_top.1 hs, ← nonempty_iff_univ_nonempty]
instance instNontrivialFilter [Nonempty α] : Nontrivial (Filter α) :=
⟨⟨⊤, ⊥, instNeBotTop.ne⟩⟩
theorem nontrivial_iff_nonempty : Nontrivial (Filter α) ↔ Nonempty α :=
⟨fun _ =>
by_contra fun h' =>
haveI := not_nonempty_iff.1 h'
not_subsingleton (Filter α) inferInstance,
@Filter.instNontrivialFilter α⟩
theorem eq_sInf_of_mem_iff_exists_mem {S : Set (Filter α)} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ f ∈ S, s ∈ f) : l = sInf S :=
le_antisymm (le_sInf fun f hf _ hs => h.2 ⟨f, hf, hs⟩)
fun _ hs => let ⟨_, hf, hs⟩ := h.1 hs; (sInf_le hf) hs
theorem eq_iInf_of_mem_iff_exists_mem {f : ι → Filter α} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ i, s ∈ f i) : l = iInf f :=
eq_sInf_of_mem_iff_exists_mem <| h.trans (exists_range_iff (p := (_ ∈ ·))).symm
theorem eq_biInf_of_mem_iff_exists_mem {f : ι → Filter α} {p : ι → Prop} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ i, p i ∧ s ∈ f i) : l = ⨅ (i) (_ : p i), f i := by
rw [iInf_subtype']
exact eq_iInf_of_mem_iff_exists_mem fun {_} => by simp only [Subtype.exists, h, exists_prop]
theorem iInf_sets_eq {f : ι → Filter α} (h : Directed (· ≥ ·) f) [ne : Nonempty ι] :
(iInf f).sets = ⋃ i, (f i).sets :=
let ⟨i⟩ := ne
let u :=
{ sets := ⋃ i, (f i).sets
univ_sets := mem_iUnion.2 ⟨i, univ_mem⟩
sets_of_superset := by
simp only [mem_iUnion, exists_imp]
exact fun i hx hxy => ⟨i, mem_of_superset hx hxy⟩
inter_sets := by
simp only [mem_iUnion, exists_imp]
intro x y a hx b hy
rcases h a b with ⟨c, ha, hb⟩
exact ⟨c, inter_mem (ha hx) (hb hy)⟩ }
have : u = iInf f := eq_iInf_of_mem_iff_exists_mem mem_iUnion
congr_arg Filter.sets this.symm
theorem mem_iInf_of_directed {f : ι → Filter α} (h : Directed (· ≥ ·) f) [Nonempty ι] (s) :
s ∈ iInf f ↔ ∃ i, s ∈ f i := by
simp only [← Filter.mem_sets, iInf_sets_eq h, mem_iUnion]
theorem mem_biInf_of_directed {f : β → Filter α} {s : Set β} (h : DirectedOn (f ⁻¹'o (· ≥ ·)) s)
(ne : s.Nonempty) {t : Set α} : (t ∈ ⨅ i ∈ s, f i) ↔ ∃ i ∈ s, t ∈ f i := by
haveI := ne.to_subtype
simp_rw [iInf_subtype', mem_iInf_of_directed h.directed_val, Subtype.exists, exists_prop]
theorem biInf_sets_eq {f : β → Filter α} {s : Set β} (h : DirectedOn (f ⁻¹'o (· ≥ ·)) s)
(ne : s.Nonempty) : (⨅ i ∈ s, f i).sets = ⋃ i ∈ s, (f i).sets :=
ext fun t => by simp [mem_biInf_of_directed h ne]
@[simp]
theorem sup_join {f₁ f₂ : Filter (Filter α)} : join f₁ ⊔ join f₂ = join (f₁ ⊔ f₂) :=
Filter.ext fun x => by simp only [mem_sup, mem_join]
@[simp]
theorem iSup_join {ι : Sort w} {f : ι → Filter (Filter α)} : ⨆ x, join (f x) = join (⨆ x, f x) :=
Filter.ext fun x => by simp only [mem_iSup, mem_join]
instance : DistribLattice (Filter α) :=
{ Filter.instCompleteLatticeFilter with
le_sup_inf := by
intro x y z s
simp only [and_assoc, mem_inf_iff, mem_sup, exists_prop, exists_imp, and_imp]
rintro hs t₁ ht₁ t₂ ht₂ rfl
exact
⟨t₁, x.sets_of_superset hs inter_subset_left, ht₁, t₂,
x.sets_of_superset hs inter_subset_right, ht₂, rfl⟩ }
/-- If `f : ι → Filter α` is directed, `ι` is not empty, and `∀ i, f i ≠ ⊥`, then `iInf f ≠ ⊥`.
See also `iInf_neBot_of_directed` for a version assuming `Nonempty α` instead of `Nonempty ι`. -/
theorem iInf_neBot_of_directed' {f : ι → Filter α} [Nonempty ι] (hd : Directed (· ≥ ·) f) :
(∀ i, NeBot (f i)) → NeBot (iInf f) :=
not_imp_not.1 <| by simpa only [not_forall, not_neBot, ← empty_mem_iff_bot,
mem_iInf_of_directed hd] using id
/-- If `f : ι → Filter α` is directed, `α` is not empty, and `∀ i, f i ≠ ⊥`, then `iInf f ≠ ⊥`.
See also `iInf_neBot_of_directed'` for a version assuming `Nonempty ι` instead of `Nonempty α`. -/
theorem iInf_neBot_of_directed {f : ι → Filter α} [hn : Nonempty α] (hd : Directed (· ≥ ·) f)
(hb : ∀ i, NeBot (f i)) : NeBot (iInf f) := by
cases isEmpty_or_nonempty ι
· constructor
simp [iInf_of_empty f, top_ne_bot]
· exact iInf_neBot_of_directed' hd hb
theorem sInf_neBot_of_directed' {s : Set (Filter α)} (hne : s.Nonempty) (hd : DirectedOn (· ≥ ·) s)
(hbot : ⊥ ∉ s) : NeBot (sInf s) :=
(sInf_eq_iInf' s).symm ▸
@iInf_neBot_of_directed' _ _ _ hne.to_subtype hd.directed_val fun ⟨_, hf⟩ =>
⟨ne_of_mem_of_not_mem hf hbot⟩
theorem sInf_neBot_of_directed [Nonempty α] {s : Set (Filter α)} (hd : DirectedOn (· ≥ ·) s)
(hbot : ⊥ ∉ s) : NeBot (sInf s) :=
(sInf_eq_iInf' s).symm ▸
iInf_neBot_of_directed hd.directed_val fun ⟨_, hf⟩ => ⟨ne_of_mem_of_not_mem hf hbot⟩
theorem iInf_neBot_iff_of_directed' {f : ι → Filter α} [Nonempty ι] (hd : Directed (· ≥ ·) f) :
NeBot (iInf f) ↔ ∀ i, NeBot (f i) :=
⟨fun H i => H.mono (iInf_le _ i), iInf_neBot_of_directed' hd⟩
theorem iInf_neBot_iff_of_directed {f : ι → Filter α} [Nonempty α] (hd : Directed (· ≥ ·) f) :
NeBot (iInf f) ↔ ∀ i, NeBot (f i) :=
⟨fun H i => H.mono (iInf_le _ i), iInf_neBot_of_directed hd⟩
/-! #### `principal` equations -/
@[simp]
theorem inf_principal {s t : Set α} : 𝓟 s ⊓ 𝓟 t = 𝓟 (s ∩ t) :=
le_antisymm
(by simp only [le_principal_iff, mem_inf_iff]; exact ⟨s, Subset.rfl, t, Subset.rfl, rfl⟩)
(by simp [le_inf_iff, inter_subset_left, inter_subset_right])
@[simp]
theorem sup_principal {s t : Set α} : 𝓟 s ⊔ 𝓟 t = 𝓟 (s ∪ t) :=
Filter.ext fun u => by simp only [union_subset_iff, mem_sup, mem_principal]
@[simp]
theorem iSup_principal {ι : Sort w} {s : ι → Set α} : ⨆ x, 𝓟 (s x) = 𝓟 (⋃ i, s i) :=
Filter.ext fun x => by simp only [mem_iSup, mem_principal, iUnion_subset_iff]
@[simp]
theorem principal_eq_bot_iff {s : Set α} : 𝓟 s = ⊥ ↔ s = ∅ :=
empty_mem_iff_bot.symm.trans <| mem_principal.trans subset_empty_iff
@[simp]
theorem principal_neBot_iff {s : Set α} : NeBot (𝓟 s) ↔ s.Nonempty :=
neBot_iff.trans <| (not_congr principal_eq_bot_iff).trans nonempty_iff_ne_empty.symm
alias ⟨_, _root_.Set.Nonempty.principal_neBot⟩ := principal_neBot_iff
theorem isCompl_principal (s : Set α) : IsCompl (𝓟 s) (𝓟 sᶜ) :=
IsCompl.of_eq (by rw [inf_principal, inter_compl_self, principal_empty]) <| by
rw [sup_principal, union_compl_self, principal_univ]
theorem mem_inf_principal' {f : Filter α} {s t : Set α} : s ∈ f ⊓ 𝓟 t ↔ tᶜ ∪ s ∈ f := by
simp only [← le_principal_iff, (isCompl_principal s).le_left_iff, disjoint_assoc, inf_principal,
← (isCompl_principal (t ∩ sᶜ)).le_right_iff, compl_inter, compl_compl]
lemma mem_inf_principal {f : Filter α} {s t : Set α} : s ∈ f ⊓ 𝓟 t ↔ { x | x ∈ t → x ∈ s } ∈ f := by
simp only [mem_inf_principal', imp_iff_not_or, setOf_or, compl_def, setOf_mem_eq]
lemma iSup_inf_principal (f : ι → Filter α) (s : Set α) : ⨆ i, f i ⊓ 𝓟 s = (⨆ i, f i) ⊓ 𝓟 s := by
ext
simp only [mem_iSup, mem_inf_principal]
theorem inf_principal_eq_bot {f : Filter α} {s : Set α} : f ⊓ 𝓟 s = ⊥ ↔ sᶜ ∈ f := by
rw [← empty_mem_iff_bot, mem_inf_principal]
simp only [mem_empty_iff_false, imp_false, compl_def]
theorem mem_of_eq_bot {f : Filter α} {s : Set α} (h : f ⊓ 𝓟 sᶜ = ⊥) : s ∈ f := by
rwa [inf_principal_eq_bot, compl_compl] at h
theorem diff_mem_inf_principal_compl {f : Filter α} {s : Set α} (hs : s ∈ f) (t : Set α) :
s \ t ∈ f ⊓ 𝓟 tᶜ :=
inter_mem_inf hs <| mem_principal_self tᶜ
theorem principal_le_iff {s : Set α} {f : Filter α} : 𝓟 s ≤ f ↔ ∀ V ∈ f, s ⊆ V := by
simp_rw [le_def, mem_principal]
end Lattice
@[mono, gcongr]
theorem join_mono {f₁ f₂ : Filter (Filter α)} (h : f₁ ≤ f₂) : join f₁ ≤ join f₂ := fun _ hs => h hs
/-! ### Eventually -/
theorem eventually_iff {f : Filter α} {P : α → Prop} : (∀ᶠ x in f, P x) ↔ { x | P x } ∈ f :=
Iff.rfl
@[simp]
theorem eventually_mem_set {s : Set α} {l : Filter α} : (∀ᶠ x in l, x ∈ s) ↔ s ∈ l :=
Iff.rfl
protected theorem ext' {f₁ f₂ : Filter α}
(h : ∀ p : α → Prop, (∀ᶠ x in f₁, p x) ↔ ∀ᶠ x in f₂, p x) : f₁ = f₂ :=
Filter.ext h
theorem Eventually.filter_mono {f₁ f₂ : Filter α} (h : f₁ ≤ f₂) {p : α → Prop}
(hp : ∀ᶠ x in f₂, p x) : ∀ᶠ x in f₁, p x :=
h hp
theorem eventually_of_mem {f : Filter α} {P : α → Prop} {U : Set α} (hU : U ∈ f)
(h : ∀ x ∈ U, P x) : ∀ᶠ x in f, P x :=
mem_of_superset hU h
protected theorem Eventually.and {p q : α → Prop} {f : Filter α} :
f.Eventually p → f.Eventually q → ∀ᶠ x in f, p x ∧ q x :=
inter_mem
@[simp] theorem eventually_true (f : Filter α) : ∀ᶠ _ in f, True := univ_mem
theorem Eventually.of_forall {p : α → Prop} {f : Filter α} (hp : ∀ x, p x) : ∀ᶠ x in f, p x :=
univ_mem' hp
@[simp]
theorem eventually_false_iff_eq_bot {f : Filter α} : (∀ᶠ _ in f, False) ↔ f = ⊥ :=
empty_mem_iff_bot
@[simp]
theorem eventually_const {f : Filter α} [t : NeBot f] {p : Prop} : (∀ᶠ _ in f, p) ↔ p := by
by_cases h : p <;> simp [h, t.ne]
theorem eventually_iff_exists_mem {p : α → Prop} {f : Filter α} :
(∀ᶠ x in f, p x) ↔ ∃ v ∈ f, ∀ y ∈ v, p y :=
exists_mem_subset_iff.symm
theorem Eventually.exists_mem {p : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x) :
∃ v ∈ f, ∀ y ∈ v, p y :=
eventually_iff_exists_mem.1 hp
theorem Eventually.mp {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∀ᶠ x in f, p x → q x) : ∀ᶠ x in f, q x :=
mp_mem hp hq
theorem Eventually.mono {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∀ x, p x → q x) : ∀ᶠ x in f, q x :=
hp.mp (Eventually.of_forall hq)
theorem forall_eventually_of_eventually_forall {f : Filter α} {p : α → β → Prop}
(h : ∀ᶠ x in f, ∀ y, p x y) : ∀ y, ∀ᶠ x in f, p x y :=
fun y => h.mono fun _ h => h y
@[simp]
theorem eventually_and {p q : α → Prop} {f : Filter α} :
(∀ᶠ x in f, p x ∧ q x) ↔ (∀ᶠ x in f, p x) ∧ ∀ᶠ x in f, q x :=
inter_mem_iff
theorem Eventually.congr {f : Filter α} {p q : α → Prop} (h' : ∀ᶠ x in f, p x)
(h : ∀ᶠ x in f, p x ↔ q x) : ∀ᶠ x in f, q x :=
h'.mp (h.mono fun _ hx => hx.mp)
theorem eventually_congr {f : Filter α} {p q : α → Prop} (h : ∀ᶠ x in f, p x ↔ q x) :
(∀ᶠ x in f, p x) ↔ ∀ᶠ x in f, q x :=
⟨fun hp => hp.congr h, fun hq => hq.congr <| by simpa only [Iff.comm] using h⟩
@[simp]
theorem eventually_or_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∀ᶠ x in f, p ∨ q x) ↔ p ∨ ∀ᶠ x in f, q x :=
by_cases (fun h : p => by simp [h]) fun h => by simp [h]
@[simp]
theorem eventually_or_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∀ᶠ x in f, p x ∨ q) ↔ (∀ᶠ x in f, p x) ∨ q := by
simp only [@or_comm _ q, eventually_or_distrib_left]
theorem eventually_imp_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∀ᶠ x in f, p → q x) ↔ p → ∀ᶠ x in f, q x := by
simp only [imp_iff_not_or, eventually_or_distrib_left]
@[simp]
theorem eventually_bot {p : α → Prop} : ∀ᶠ x in ⊥, p x :=
⟨⟩
@[simp]
theorem eventually_top {p : α → Prop} : (∀ᶠ x in ⊤, p x) ↔ ∀ x, p x :=
Iff.rfl
@[simp]
theorem eventually_sup {p : α → Prop} {f g : Filter α} :
(∀ᶠ x in f ⊔ g, p x) ↔ (∀ᶠ x in f, p x) ∧ ∀ᶠ x in g, p x :=
Iff.rfl
@[simp]
theorem eventually_sSup {p : α → Prop} {fs : Set (Filter α)} :
(∀ᶠ x in sSup fs, p x) ↔ ∀ f ∈ fs, ∀ᶠ x in f, p x :=
Iff.rfl
@[simp]
theorem eventually_iSup {p : α → Prop} {fs : ι → Filter α} :
(∀ᶠ x in ⨆ b, fs b, p x) ↔ ∀ b, ∀ᶠ x in fs b, p x :=
mem_iSup
@[simp]
theorem eventually_principal {a : Set α} {p : α → Prop} : (∀ᶠ x in 𝓟 a, p x) ↔ ∀ x ∈ a, p x :=
Iff.rfl
theorem Eventually.forall_mem {α : Type*} {f : Filter α} {s : Set α} {P : α → Prop}
(hP : ∀ᶠ x in f, P x) (hf : 𝓟 s ≤ f) : ∀ x ∈ s, P x :=
Filter.eventually_principal.mp (hP.filter_mono hf)
theorem eventually_inf {f g : Filter α} {p : α → Prop} :
(∀ᶠ x in f ⊓ g, p x) ↔ ∃ s ∈ f, ∃ t ∈ g, ∀ x ∈ s ∩ t, p x :=
mem_inf_iff_superset
theorem eventually_inf_principal {f : Filter α} {p : α → Prop} {s : Set α} :
(∀ᶠ x in f ⊓ 𝓟 s, p x) ↔ ∀ᶠ x in f, x ∈ s → p x :=
mem_inf_principal
theorem eventually_iff_all_subsets {f : Filter α} {p : α → Prop} :
(∀ᶠ x in f, p x) ↔ ∀ (s : Set α), ∀ᶠ x in f, x ∈ s → p x where
mp h _ := by filter_upwards [h] with _ pa _ using pa
mpr h := by filter_upwards [h univ] with _ pa using pa (by simp)
/-! ### Frequently -/
theorem Eventually.frequently {f : Filter α} [NeBot f] {p : α → Prop} (h : ∀ᶠ x in f, p x) :
∃ᶠ x in f, p x :=
compl_not_mem h
theorem Frequently.of_forall {f : Filter α} [NeBot f] {p : α → Prop} (h : ∀ x, p x) :
∃ᶠ x in f, p x :=
Eventually.frequently (Eventually.of_forall h)
theorem Frequently.mp {p q : α → Prop} {f : Filter α} (h : ∃ᶠ x in f, p x)
(hpq : ∀ᶠ x in f, p x → q x) : ∃ᶠ x in f, q x :=
mt (fun hq => hq.mp <| hpq.mono fun _ => mt) h
lemma frequently_congr {p q : α → Prop} {f : Filter α} (h : ∀ᶠ x in f, p x ↔ q x) :
(∃ᶠ x in f, p x) ↔ ∃ᶠ x in f, q x :=
⟨fun h' ↦ h'.mp (h.mono fun _ ↦ Iff.mp), fun h' ↦ h'.mp (h.mono fun _ ↦ Iff.mpr)⟩
theorem Frequently.filter_mono {p : α → Prop} {f g : Filter α} (h : ∃ᶠ x in f, p x) (hle : f ≤ g) :
∃ᶠ x in g, p x :=
mt (fun h' => h'.filter_mono hle) h
theorem Frequently.mono {p q : α → Prop} {f : Filter α} (h : ∃ᶠ x in f, p x)
(hpq : ∀ x, p x → q x) : ∃ᶠ x in f, q x :=
h.mp (Eventually.of_forall hpq)
theorem Frequently.and_eventually {p q : α → Prop} {f : Filter α} (hp : ∃ᶠ x in f, p x)
(hq : ∀ᶠ x in f, q x) : ∃ᶠ x in f, p x ∧ q x := by
refine mt (fun h => hq.mp <| h.mono ?_) hp
exact fun x hpq hq hp => hpq ⟨hp, hq⟩
theorem Eventually.and_frequently {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∃ᶠ x in f, q x) : ∃ᶠ x in f, p x ∧ q x := by
simpa only [and_comm] using hq.and_eventually hp
theorem Frequently.exists {p : α → Prop} {f : Filter α} (hp : ∃ᶠ x in f, p x) : ∃ x, p x := by
by_contra H
replace H : ∀ᶠ x in f, ¬p x := Eventually.of_forall (not_exists.1 H)
exact hp H
theorem Eventually.exists {p : α → Prop} {f : Filter α} [NeBot f] (hp : ∀ᶠ x in f, p x) :
∃ x, p x :=
hp.frequently.exists
lemma frequently_iff_neBot {l : Filter α} {p : α → Prop} :
(∃ᶠ x in l, p x) ↔ NeBot (l ⊓ 𝓟 {x | p x}) := by
rw [neBot_iff, Ne, inf_principal_eq_bot]; rfl
lemma frequently_mem_iff_neBot {l : Filter α} {s : Set α} : (∃ᶠ x in l, x ∈ s) ↔ NeBot (l ⊓ 𝓟 s) :=
frequently_iff_neBot
theorem frequently_iff_forall_eventually_exists_and {p : α → Prop} {f : Filter α} :
(∃ᶠ x in f, p x) ↔ ∀ {q : α → Prop}, (∀ᶠ x in f, q x) → ∃ x, p x ∧ q x :=
⟨fun hp _ hq => (hp.and_eventually hq).exists, fun H hp => by
simpa only [and_not_self_iff, exists_false] using H hp⟩
theorem frequently_iff {f : Filter α} {P : α → Prop} :
(∃ᶠ x in f, P x) ↔ ∀ {U}, U ∈ f → ∃ x ∈ U, P x := by
simp only [frequently_iff_forall_eventually_exists_and, @and_comm (P _)]
rfl
@[simp]
theorem not_eventually {p : α → Prop} {f : Filter α} : (¬∀ᶠ x in f, p x) ↔ ∃ᶠ x in f, ¬p x := by
simp [Filter.Frequently]
@[simp]
theorem not_frequently {p : α → Prop} {f : Filter α} : (¬∃ᶠ x in f, p x) ↔ ∀ᶠ x in f, ¬p x := by
simp only [Filter.Frequently, not_not]
@[simp]
theorem frequently_true_iff_neBot (f : Filter α) : (∃ᶠ _ in f, True) ↔ NeBot f := by
simp [frequently_iff_neBot]
@[simp]
theorem frequently_false (f : Filter α) : ¬∃ᶠ _ in f, False := by simp
@[simp]
theorem frequently_const {f : Filter α} [NeBot f] {p : Prop} : (∃ᶠ _ in f, p) ↔ p := by
by_cases p <;> simp [*]
@[simp]
theorem frequently_or_distrib {f : Filter α} {p q : α → Prop} :
(∃ᶠ x in f, p x ∨ q x) ↔ (∃ᶠ x in f, p x) ∨ ∃ᶠ x in f, q x := by
simp only [Filter.Frequently, ← not_and_or, not_or, eventually_and]
theorem frequently_or_distrib_left {f : Filter α} [NeBot f] {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p ∨ q x) ↔ p ∨ ∃ᶠ x in f, q x := by simp
theorem frequently_or_distrib_right {f : Filter α} [NeBot f] {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x ∨ q) ↔ (∃ᶠ x in f, p x) ∨ q := by simp
theorem frequently_imp_distrib {f : Filter α} {p q : α → Prop} :
(∃ᶠ x in f, p x → q x) ↔ (∀ᶠ x in f, p x) → ∃ᶠ x in f, q x := by
simp [imp_iff_not_or]
theorem frequently_imp_distrib_left {f : Filter α} [NeBot f] {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p → q x) ↔ p → ∃ᶠ x in f, q x := by simp [frequently_imp_distrib]
theorem frequently_imp_distrib_right {f : Filter α} [NeBot f] {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x → q) ↔ (∀ᶠ x in f, p x) → q := by
simp only [frequently_imp_distrib, frequently_const]
theorem eventually_imp_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∀ᶠ x in f, p x → q) ↔ (∃ᶠ x in f, p x) → q := by
simp only [imp_iff_not_or, eventually_or_distrib_right, not_frequently]
@[simp]
theorem frequently_and_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p ∧ q x) ↔ p ∧ ∃ᶠ x in f, q x := by
simp only [Filter.Frequently, not_and, eventually_imp_distrib_left, Classical.not_imp]
@[simp]
theorem frequently_and_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x ∧ q) ↔ (∃ᶠ x in f, p x) ∧ q := by
simp only [@and_comm _ q, frequently_and_distrib_left]
@[simp]
theorem frequently_bot {p : α → Prop} : ¬∃ᶠ x in ⊥, p x := by simp
@[simp]
theorem frequently_top {p : α → Prop} : (∃ᶠ x in ⊤, p x) ↔ ∃ x, p x := by simp [Filter.Frequently]
@[simp]
theorem frequently_principal {a : Set α} {p : α → Prop} : (∃ᶠ x in 𝓟 a, p x) ↔ ∃ x ∈ a, p x := by
simp [Filter.Frequently, not_forall]
theorem frequently_inf_principal {f : Filter α} {s : Set α} {p : α → Prop} :
(∃ᶠ x in f ⊓ 𝓟 s, p x) ↔ ∃ᶠ x in f, x ∈ s ∧ p x := by
simp only [Filter.Frequently, eventually_inf_principal, not_and]
alias ⟨Frequently.of_inf_principal, Frequently.inf_principal⟩ := frequently_inf_principal
theorem frequently_sup {p : α → Prop} {f g : Filter α} :
(∃ᶠ x in f ⊔ g, p x) ↔ (∃ᶠ x in f, p x) ∨ ∃ᶠ x in g, p x := by
simp only [Filter.Frequently, eventually_sup, not_and_or]
@[simp]
theorem frequently_sSup {p : α → Prop} {fs : Set (Filter α)} :
(∃ᶠ x in sSup fs, p x) ↔ ∃ f ∈ fs, ∃ᶠ x in f, p x := by
simp only [Filter.Frequently, not_forall, eventually_sSup, exists_prop]
@[simp]
theorem frequently_iSup {p : α → Prop} {fs : β → Filter α} :
(∃ᶠ x in ⨆ b, fs b, p x) ↔ ∃ b, ∃ᶠ x in fs b, p x := by
simp only [Filter.Frequently, eventually_iSup, not_forall]
theorem Eventually.choice {r : α → β → Prop} {l : Filter α} [l.NeBot] (h : ∀ᶠ x in l, ∃ y, r x y) :
∃ f : α → β, ∀ᶠ x in l, r x (f x) := by
haveI : Nonempty β := let ⟨_, hx⟩ := h.exists; hx.nonempty
choose! f hf using fun x (hx : ∃ y, r x y) => hx
exact ⟨f, h.mono hf⟩
lemma skolem {ι : Type*} {α : ι → Type*} [∀ i, Nonempty (α i)]
{P : ∀ i : ι, α i → Prop} {F : Filter ι} :
(∀ᶠ i in F, ∃ b, P i b) ↔ ∃ b : (Π i, α i), ∀ᶠ i in F, P i (b i) := by
classical
refine ⟨fun H ↦ ?_, fun ⟨b, hb⟩ ↦ hb.mp (.of_forall fun x a ↦ ⟨_, a⟩)⟩
refine ⟨fun i ↦ if h : ∃ b, P i b then h.choose else Nonempty.some inferInstance, ?_⟩
filter_upwards [H] with i hi
exact dif_pos hi ▸ hi.choose_spec
/-!
### Relation “eventually equal”
-/
section EventuallyEq
variable {l : Filter α} {f g : α → β}
| Mathlib/Order/Filter/Basic.lean | 862 | 865 | theorem EventuallyEq.eventually (h : f =ᶠ[l] g) : ∀ᶠ x in l, f x = g x := h
@[simp] lemma eventuallyEq_top : f =ᶠ[⊤] g ↔ f = g := by | simp [EventuallyEq, funext_iff] |
/-
Copyright (c) 2019 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison, Yaël Dillies
-/
import Mathlib.Order.Cover
import Mathlib.Order.Interval.Finset.Defs
/-!
# Intervals as finsets
This file provides basic results about all the `Finset.Ixx`, which are defined in
`Order.Interval.Finset.Defs`.
In addition, it shows that in a locally finite order `≤` and `<` are the transitive closures of,
respectively, `⩿` and `⋖`, which then leads to a characterization of monotone and strictly
functions whose domain is a locally finite order. In particular, this file proves:
* `le_iff_transGen_wcovBy`: `≤` is the transitive closure of `⩿`
* `lt_iff_transGen_covBy`: `<` is the transitive closure of `⋖`
* `monotone_iff_forall_wcovBy`: Characterization of monotone functions
* `strictMono_iff_forall_covBy`: Characterization of strictly monotone functions
## TODO
This file was originally only about `Finset.Ico a b` where `a b : ℕ`. No care has yet been taken to
generalize these lemmas properly and many lemmas about `Icc`, `Ioc`, `Ioo` are missing. In general,
what's to do is taking the lemmas in `Data.X.Intervals` and abstract away the concrete structure.
Complete the API. See
https://github.com/leanprover-community/mathlib/pull/14448#discussion_r906109235
for some ideas.
-/
assert_not_exists MonoidWithZero Finset.sum
open Function OrderDual
open FinsetInterval
variable {ι α : Type*} {a a₁ a₂ b b₁ b₂ c x : α}
namespace Finset
section Preorder
variable [Preorder α]
section LocallyFiniteOrder
variable [LocallyFiniteOrder α]
@[simp]
theorem nonempty_Icc : (Icc a b).Nonempty ↔ a ≤ b := by
rw [← coe_nonempty, coe_Icc, Set.nonempty_Icc]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Icc_of_le⟩ := nonempty_Icc
@[simp]
theorem nonempty_Ico : (Ico a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ico, Set.nonempty_Ico]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ico_of_lt⟩ := nonempty_Ico
@[simp]
theorem nonempty_Ioc : (Ioc a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ioc, Set.nonempty_Ioc]
@[aesop safe apply (rule_sets := [finsetNonempty])]
alias ⟨_, Aesop.nonempty_Ioc_of_lt⟩ := nonempty_Ioc
-- TODO: This is nonsense. A locally finite order is never densely ordered
@[simp]
theorem nonempty_Ioo [DenselyOrdered α] : (Ioo a b).Nonempty ↔ a < b := by
rw [← coe_nonempty, coe_Ioo, Set.nonempty_Ioo]
@[simp]
theorem Icc_eq_empty_iff : Icc a b = ∅ ↔ ¬a ≤ b := by
rw [← coe_eq_empty, coe_Icc, Set.Icc_eq_empty_iff]
@[simp]
theorem Ico_eq_empty_iff : Ico a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ico, Set.Ico_eq_empty_iff]
@[simp]
theorem Ioc_eq_empty_iff : Ioc a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ioc, Set.Ioc_eq_empty_iff]
-- TODO: This is nonsense. A locally finite order is never densely ordered
@[simp]
theorem Ioo_eq_empty_iff [DenselyOrdered α] : Ioo a b = ∅ ↔ ¬a < b := by
rw [← coe_eq_empty, coe_Ioo, Set.Ioo_eq_empty_iff]
alias ⟨_, Icc_eq_empty⟩ := Icc_eq_empty_iff
alias ⟨_, Ico_eq_empty⟩ := Ico_eq_empty_iff
alias ⟨_, Ioc_eq_empty⟩ := Ioc_eq_empty_iff
@[simp]
theorem Ioo_eq_empty (h : ¬a < b) : Ioo a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ hx => h ((mem_Ioo.1 hx).1.trans (mem_Ioo.1 hx).2)
@[simp]
theorem Icc_eq_empty_of_lt (h : b < a) : Icc a b = ∅ :=
Icc_eq_empty h.not_le
@[simp]
theorem Ico_eq_empty_of_le (h : b ≤ a) : Ico a b = ∅ :=
Ico_eq_empty h.not_lt
@[simp]
theorem Ioc_eq_empty_of_le (h : b ≤ a) : Ioc a b = ∅ :=
Ioc_eq_empty h.not_lt
@[simp]
theorem Ioo_eq_empty_of_le (h : b ≤ a) : Ioo a b = ∅ :=
Ioo_eq_empty h.not_lt
theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, true_and, le_rfl]
theorem left_mem_Ico : a ∈ Ico a b ↔ a < b := by simp only [mem_Ico, true_and, le_refl]
theorem right_mem_Icc : b ∈ Icc a b ↔ a ≤ b := by simp only [mem_Icc, and_true, le_rfl]
theorem right_mem_Ioc : b ∈ Ioc a b ↔ a < b := by simp only [mem_Ioc, and_true, le_rfl]
theorem left_not_mem_Ioc : a ∉ Ioc a b := fun h => lt_irrefl _ (mem_Ioc.1 h).1
theorem left_not_mem_Ioo : a ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).1
theorem right_not_mem_Ico : b ∉ Ico a b := fun h => lt_irrefl _ (mem_Ico.1 h).2
theorem right_not_mem_Ioo : b ∉ Ioo a b := fun h => lt_irrefl _ (mem_Ioo.1 h).2
@[gcongr]
| Mathlib/Order/Interval/Finset/Basic.lean | 139 | 139 | theorem Icc_subset_Icc (ha : a₂ ≤ a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊆ Icc a₂ b₂ := by | |
/-
Copyright (c) 2023 Dagur Asgeirsson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Dagur Asgeirsson, Filippo A. E. Nuccio, Riccardo Brasca
-/
import Mathlib.CategoryTheory.EffectiveEpi.Preserves
import Mathlib.CategoryTheory.Limits.Final.ParallelPair
import Mathlib.CategoryTheory.Preadditive.Projective.Basic
import Mathlib.CategoryTheory.Sites.Canonical
import Mathlib.CategoryTheory.Sites.Coherent.Basic
import Mathlib.CategoryTheory.Sites.EffectiveEpimorphic
/-!
# Sheaves for the regular topology
This file characterises sheaves for the regular topology.
## Main results
* `equalizerCondition_iff_isSheaf`: In a preregular category with pullbacks, the sheaves for the
regular topology are precisely the presheaves satisfying an equaliser condition with respect to
effective epimorphisms.
* `isSheaf_of_projective`: In a preregular category in which every object is projective, every
presheaf is a sheaf for the regular topology.
-/
namespace CategoryTheory
open Limits
variable {C D E : Type*} [Category C] [Category D] [Category E]
open Opposite Presieve Functor
/-- A presieve is *regular* if it consists of a single effective epimorphism. -/
class Presieve.regular {X : C} (R : Presieve X) : Prop where
/-- `R` consists of a single epimorphism. -/
single_epi : ∃ (Y : C) (f : Y ⟶ X), R = Presieve.ofArrows (fun (_ : Unit) ↦ Y)
(fun (_ : Unit) ↦ f) ∧ EffectiveEpi f
namespace regularTopology
lemma equalizerCondition_w (P : Cᵒᵖ ⥤ D) {X B : C} {π : X ⟶ B} (c : PullbackCone π π) :
P.map π.op ≫ P.map c.fst.op = P.map π.op ≫ P.map c.snd.op := by
simp only [← Functor.map_comp, ← op_comp, c.condition]
/--
A contravariant functor on `C` satisfies `SingleEqualizerCondition` with respect to a morphism `π`
if it takes its kernel pair to an equalizer diagram.
-/
def SingleEqualizerCondition (P : Cᵒᵖ ⥤ D) ⦃X B : C⦄ (π : X ⟶ B) : Prop :=
∀ (c : PullbackCone π π) (_ : IsLimit c),
Nonempty (IsLimit (Fork.ofι (P.map π.op) (equalizerCondition_w P c)))
/--
A contravariant functor on `C` satisfies `EqualizerCondition` if it takes kernel pairs of effective
epimorphisms to equalizer diagrams.
-/
def EqualizerCondition (P : Cᵒᵖ ⥤ D) : Prop :=
∀ ⦃X B : C⦄ (π : X ⟶ B) [EffectiveEpi π], SingleEqualizerCondition P π
/-- The equalizer condition is preserved by natural isomorphism. -/
theorem equalizerCondition_of_natIso {P P' : Cᵒᵖ ⥤ D} (i : P ≅ P')
(hP : EqualizerCondition P) : EqualizerCondition P' := fun X B π _ c hc ↦
⟨Fork.isLimitOfIsos _ (hP π c hc).some _ (i.app _) (i.app _) (i.app _)⟩
/-- Precomposing with a pullback-preserving functor preserves the equalizer condition. -/
theorem equalizerCondition_precomp_of_preservesPullback (P : Cᵒᵖ ⥤ D) (F : E ⥤ C)
[∀ {X B} (π : X ⟶ B) [EffectiveEpi π], PreservesLimit (cospan π π) F]
[F.PreservesEffectiveEpis] (hP : EqualizerCondition P) : EqualizerCondition (F.op ⋙ P) := by
intro X B π _ c hc
have h : P.map (F.map π).op = (F.op ⋙ P).map π.op := by simp
refine ⟨(IsLimit.equivIsoLimit (ForkOfι.ext ?_ _ h)) ?_⟩
· simp only [Functor.comp_map, op_map, Quiver.Hom.unop_op, ← map_comp, ← op_comp, c.condition]
· refine (hP (F.map π) (PullbackCone.mk (F.map c.fst) (F.map c.snd) ?_) ?_).some
· simp only [← map_comp, c.condition]
· exact (isLimitMapConePullbackConeEquiv F c.condition)
(isLimitOfPreserves F (hc.ofIsoLimit (PullbackCone.ext (Iso.refl _) (by simp) (by simp))))
/-- The canonical map to the explicit equalizer. -/
def MapToEqualizer (P : Cᵒᵖ ⥤ Type*) {W X B : C} (f : X ⟶ B)
(g₁ g₂ : W ⟶ X) (w : g₁ ≫ f = g₂ ≫ f) :
P.obj (op B) → { x : P.obj (op X) | P.map g₁.op x = P.map g₂.op x } := fun t ↦
⟨P.map f.op t, by simp only [Set.mem_setOf_eq, ← FunctorToTypes.map_comp_apply, ← op_comp, w]⟩
| Mathlib/CategoryTheory/Sites/Coherent/RegularSheaves.lean | 87 | 100 | theorem EqualizerCondition.bijective_mapToEqualizer_pullback (P : Cᵒᵖ ⥤ Type*)
(hP : EqualizerCondition P) : ∀ (X B : C) (π : X ⟶ B) [EffectiveEpi π] [HasPullback π π],
Function.Bijective
(MapToEqualizer P π (pullback.fst π π) (pullback.snd π π) pullback.condition) := by | intro X B π _ _
specialize hP π _ (pullbackIsPullback π π)
rw [Types.type_equalizer_iff_unique] at hP
rw [Function.bijective_iff_existsUnique]
intro ⟨b, hb⟩
obtain ⟨a, ha₁, ha₂⟩ := hP b hb
refine ⟨a, ?_, ?_⟩
· simpa [MapToEqualizer] using ha₁
· simpa [MapToEqualizer] using ha₂ |
/-
Copyright (c) 2021 Kim Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kim Morrison
-/
import Mathlib.Algebra.Order.Field.Power
import Mathlib.Analysis.SpecificLimits.Basic
import Mathlib.RingTheory.Polynomial.Bernstein
import Mathlib.Topology.ContinuousMap.Polynomial
import Mathlib.Topology.ContinuousMap.Compact
/-!
# Bernstein approximations and Weierstrass' theorem
We prove that the Bernstein approximations
```
∑ k : Fin (n+1), f (k/n : ℝ) * n.choose k * x^k * (1-x)^(n-k)
```
for a continuous function `f : C([0,1], ℝ)` converge uniformly to `f` as `n` tends to infinity.
Our proof follows [Richard Beals' *Analysis, an introduction*][beals-analysis], §7D.
The original proof, due to [Bernstein](bernstein1912) in 1912, is probabilistic,
and relies on Bernoulli's theorem,
which gives bounds for how quickly the observed frequencies in a
Bernoulli trial approach the underlying probability.
The proof here does not directly rely on Bernoulli's theorem,
but can also be given a probabilistic account.
* Consider a weighted coin which with probability `x` produces heads,
and with probability `1-x` produces tails.
* The value of `bernstein n k x` is the probability that
such a coin gives exactly `k` heads in a sequence of `n` tosses.
* If such an appearance of `k` heads results in a payoff of `f(k / n)`,
the `n`-th Bernstein approximation for `f` evaluated at `x` is the expected payoff.
* The main estimate in the proof bounds the probability that
the observed frequency of heads differs from `x` by more than some `δ`,
obtaining a bound of `(4 * n * δ^2)⁻¹`, irrespective of `x`.
* This ensures that for `n` large, the Bernstein approximation is (uniformly) close to the
payoff function `f`.
(You don't need to think in these terms to follow the proof below: it's a giant `calc` block!)
This result proves Weierstrass' theorem that polynomials are dense in `C([0,1], ℝ)`,
although we defer an abstract statement of this until later.
-/
noncomputable section
open scoped BoundedContinuousFunction unitInterval
/-- The Bernstein polynomials, as continuous functions on `[0,1]`.
-/
def bernstein (n ν : ℕ) : C(I, ℝ) :=
(bernsteinPolynomial ℝ n ν).toContinuousMapOn I
@[simp]
theorem bernstein_apply (n ν : ℕ) (x : I) :
bernstein n ν x = (n.choose ν : ℝ) * (x : ℝ) ^ ν * (1 - (x : ℝ)) ^ (n - ν) := by
dsimp [bernstein, Polynomial.toContinuousMapOn, Polynomial.toContinuousMap, bernsteinPolynomial]
simp
theorem bernstein_nonneg {n ν : ℕ} {x : I} : 0 ≤ bernstein n ν x := by
simp only [bernstein_apply]
have h₁ : (0 : ℝ) ≤ x := by unit_interval
have h₂ : (0 : ℝ) ≤ 1 - x := by unit_interval
positivity
namespace Mathlib.Meta.Positivity
open Lean Meta Qq Function
/-- Extension of the `positivity` tactic for Bernstein polynomials: they are always non-negative. -/
@[positivity DFunLike.coe _ _]
def evalBernstein : PositivityExt where eval {_ _} _zα _pα e := do
let .app (.app _coe (.app (.app _ n) ν)) x ← whnfR e | throwError "not bernstein polynomial"
let p ← mkAppOptM ``bernstein_nonneg #[n, ν, x]
pure (.nonnegative p)
end Mathlib.Meta.Positivity
/-!
We now give a slight reformulation of `bernsteinPolynomial.variance`.
-/
namespace bernstein
/-- Send `k : Fin (n+1)` to the equally spaced points `k/n` in the unit interval.
-/
def z {n : ℕ} (k : Fin (n + 1)) : I :=
⟨(k : ℝ) / n, by
rcases n with - | n
· norm_num
· have h₁ : 0 < (n.succ : ℝ) := mod_cast Nat.succ_pos _
have h₂ : ↑k ≤ n.succ := mod_cast Fin.le_last k
rw [Set.mem_Icc, le_div_iff₀ h₁, div_le_iff₀ h₁]
norm_cast
simp [h₂]⟩
local postfix:90 "/ₙ" => z
theorem probability (n : ℕ) (x : I) : (∑ k : Fin (n + 1), bernstein n k x) = 1 := by
have := bernsteinPolynomial.sum ℝ n
apply_fun fun p => Polynomial.aeval (x : ℝ) p at this
simp? [map_sum, Finset.sum_range] at this says
simp only [Finset.sum_range, map_sum, Polynomial.coe_aeval_eq_eval, Polynomial.eval_one] at this
exact this
| Mathlib/Analysis/SpecialFunctions/Bernstein.lean | 109 | 114 | theorem variance {n : ℕ} (h : 0 < (n : ℝ)) (x : I) :
(∑ k : Fin (n + 1), (x - k/ₙ : ℝ) ^ 2 * bernstein n k x) = (x : ℝ) * (1 - x) / n := by | have h' : (n : ℝ) ≠ 0 := ne_of_gt h
apply_fun fun x : ℝ => x * n using GroupWithZero.mul_left_injective h'
apply_fun fun x : ℝ => x * n using GroupWithZero.mul_left_injective h'
dsimp |
/-
Copyright (c) 2020 Paul van Wamelen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Paul van Wamelen
-/
import Mathlib.Data.Nat.Factors
import Mathlib.NumberTheory.FLT.Basic
import Mathlib.NumberTheory.PythagoreanTriples
import Mathlib.RingTheory.Coprime.Lemmas
import Mathlib.Tactic.LinearCombination
/-!
# Fermat's Last Theorem for the case n = 4
There are no non-zero integers `a`, `b` and `c` such that `a ^ 4 + b ^ 4 = c ^ 4`.
-/
assert_not_exists TwoSidedIdeal
noncomputable section
/-- Shorthand for three non-zero integers `a`, `b`, and `c` satisfying `a ^ 4 + b ^ 4 = c ^ 2`.
We will show that no integers satisfy this equation. Clearly Fermat's Last theorem for n = 4
follows. -/
def Fermat42 (a b c : ℤ) : Prop :=
a ≠ 0 ∧ b ≠ 0 ∧ a ^ 4 + b ^ 4 = c ^ 2
namespace Fermat42
theorem comm {a b c : ℤ} : Fermat42 a b c ↔ Fermat42 b a c := by
delta Fermat42
rw [add_comm]
tauto
theorem mul {a b c k : ℤ} (hk0 : k ≠ 0) :
Fermat42 a b c ↔ Fermat42 (k * a) (k * b) (k ^ 2 * c) := by
delta Fermat42
constructor
· intro f42
constructor
· exact mul_ne_zero hk0 f42.1
constructor
· exact mul_ne_zero hk0 f42.2.1
· have H : a ^ 4 + b ^ 4 = c ^ 2 := f42.2.2
linear_combination k ^ 4 * H
· intro f42
constructor
· exact right_ne_zero_of_mul f42.1
constructor
· exact right_ne_zero_of_mul f42.2.1
apply (mul_right_inj' (pow_ne_zero 4 hk0)).mp
linear_combination f42.2.2
theorem ne_zero {a b c : ℤ} (h : Fermat42 a b c) : c ≠ 0 := by
apply ne_zero_pow two_ne_zero _; apply ne_of_gt
rw [← h.2.2, (by ring : a ^ 4 + b ^ 4 = (a ^ 2) ^ 2 + (b ^ 2) ^ 2)]
exact
add_pos (sq_pos_of_ne_zero (pow_ne_zero 2 h.1)) (sq_pos_of_ne_zero (pow_ne_zero 2 h.2.1))
/-- We say a solution to `a ^ 4 + b ^ 4 = c ^ 2` is minimal if there is no other solution with
a smaller `c` (in absolute value). -/
def Minimal (a b c : ℤ) : Prop :=
Fermat42 a b c ∧ ∀ a1 b1 c1 : ℤ, Fermat42 a1 b1 c1 → Int.natAbs c ≤ Int.natAbs c1
/-- if we have a solution to `a ^ 4 + b ^ 4 = c ^ 2` then there must be a minimal one. -/
theorem exists_minimal {a b c : ℤ} (h : Fermat42 a b c) : ∃ a0 b0 c0, Minimal a0 b0 c0 := by
classical
let S : Set ℕ := { n | ∃ s : ℤ × ℤ × ℤ, Fermat42 s.1 s.2.1 s.2.2 ∧ n = Int.natAbs s.2.2 }
have S_nonempty : S.Nonempty := by
use Int.natAbs c
rw [Set.mem_setOf_eq]
use ⟨a, ⟨b, c⟩⟩
let m : ℕ := Nat.find S_nonempty
have m_mem : m ∈ S := Nat.find_spec S_nonempty
rcases m_mem with ⟨s0, hs0, hs1⟩
use s0.1, s0.2.1, s0.2.2, hs0
intro a1 b1 c1 h1
rw [← hs1]
apply Nat.find_min'
use ⟨a1, ⟨b1, c1⟩⟩
/-- a minimal solution to `a ^ 4 + b ^ 4 = c ^ 2` must have `a` and `b` coprime. -/
theorem coprime_of_minimal {a b c : ℤ} (h : Minimal a b c) : IsCoprime a b := by
apply Int.isCoprime_iff_gcd_eq_one.mpr
by_contra hab
obtain ⟨p, hp, hpa, hpb⟩ := Nat.Prime.not_coprime_iff_dvd.mp hab
obtain ⟨a1, rfl⟩ := Int.natCast_dvd.mpr hpa
obtain ⟨b1, rfl⟩ := Int.natCast_dvd.mpr hpb
have hpc : (p : ℤ) ^ 2 ∣ c := by
rw [← Int.pow_dvd_pow_iff two_ne_zero, ← h.1.2.2]
apply Dvd.intro (a1 ^ 4 + b1 ^ 4)
ring
obtain ⟨c1, rfl⟩ := hpc
have hf : Fermat42 a1 b1 c1 :=
(Fermat42.mul (Int.natCast_ne_zero.mpr (Nat.Prime.ne_zero hp))).mpr h.1
apply Nat.le_lt_asymm (h.2 _ _ _ hf)
rw [Int.natAbs_mul, lt_mul_iff_one_lt_left, Int.natAbs_pow, Int.natAbs_natCast]
· exact Nat.one_lt_pow two_ne_zero (Nat.Prime.one_lt hp)
· exact Nat.pos_of_ne_zero (Int.natAbs_ne_zero.2 (ne_zero hf))
/-- We can swap `a` and `b` in a minimal solution to `a ^ 4 + b ^ 4 = c ^ 2`. -/
theorem minimal_comm {a b c : ℤ} : Minimal a b c → Minimal b a c := fun ⟨h1, h2⟩ =>
⟨Fermat42.comm.mp h1, h2⟩
/-- We can assume that a minimal solution to `a ^ 4 + b ^ 4 = c ^ 2` has positive `c`. -/
theorem neg_of_minimal {a b c : ℤ} : Minimal a b c → Minimal a b (-c) := by
rintro ⟨⟨ha, hb, heq⟩, h2⟩
constructor
· apply And.intro ha (And.intro hb _)
rw [heq]
exact (neg_sq c).symm
rwa [Int.natAbs_neg c]
/-- We can assume that a minimal solution to `a ^ 4 + b ^ 4 = c ^ 2` has `a` odd. -/
theorem exists_odd_minimal {a b c : ℤ} (h : Fermat42 a b c) :
∃ a0 b0 c0, Minimal a0 b0 c0 ∧ a0 % 2 = 1 := by
obtain ⟨a0, b0, c0, hf⟩ := exists_minimal h
rcases Int.emod_two_eq_zero_or_one a0 with hap | hap
· rcases Int.emod_two_eq_zero_or_one b0 with hbp | hbp
· exfalso
have h1 : 2 ∣ (Int.gcd a0 b0 : ℤ) :=
Int.dvd_coe_gcd (Int.dvd_of_emod_eq_zero hap) (Int.dvd_of_emod_eq_zero hbp)
rw [Int.isCoprime_iff_gcd_eq_one.mp (coprime_of_minimal hf)] at h1
revert h1
decide
· exact ⟨b0, ⟨a0, ⟨c0, minimal_comm hf, hbp⟩⟩⟩
exact ⟨a0, ⟨b0, ⟨c0, hf, hap⟩⟩⟩
/-- We can assume that a minimal solution to `a ^ 4 + b ^ 4 = c ^ 2` has
`a` odd and `c` positive. -/
theorem exists_pos_odd_minimal {a b c : ℤ} (h : Fermat42 a b c) :
∃ a0 b0 c0, Minimal a0 b0 c0 ∧ a0 % 2 = 1 ∧ 0 < c0 := by
obtain ⟨a0, b0, c0, hf, hc⟩ := exists_odd_minimal h
rcases lt_trichotomy 0 c0 with (h1 | h1 | h1)
· use a0, b0, c0
· exfalso
exact ne_zero hf.1 h1.symm
· use a0, b0, -c0, neg_of_minimal hf, hc
exact neg_pos.mpr h1
end Fermat42
theorem Int.isCoprime_of_sq_sum {r s : ℤ} (h2 : IsCoprime s r) : IsCoprime (r ^ 2 + s ^ 2) r := by
rw [sq, sq]
exact (IsCoprime.mul_left h2 h2).mul_add_left_left r
@[deprecated (since := "2025-01-23")] alias Int.coprime_of_sq_sum := Int.isCoprime_of_sq_sum
theorem Int.isCoprime_of_sq_sum' {r s : ℤ} (h : IsCoprime r s) :
IsCoprime (r ^ 2 + s ^ 2) (r * s) := by
apply IsCoprime.mul_right (Int.isCoprime_of_sq_sum (isCoprime_comm.mp h))
rw [add_comm]; apply Int.isCoprime_of_sq_sum h
@[deprecated (since := "2025-01-23")] alias Int.coprime_of_sq_sum' := Int.isCoprime_of_sq_sum'
namespace Fermat42
-- If we have a solution to a ^ 4 + b ^ 4 = c ^ 2, we can construct a smaller one. This
-- implies there can't be a smallest solution.
| Mathlib/NumberTheory/FLT/Four.lean | 159 | 162 | theorem not_minimal {a b c : ℤ} (h : Minimal a b c) (ha2 : a % 2 = 1) (hc : 0 < c) : False := by | -- Use the fact that a ^ 2, b ^ 2, c form a pythagorean triple to obtain m and n such that
-- a ^ 2 = m ^ 2 - n ^ 2, b ^ 2 = 2 * m * n and c = m ^ 2 + n ^ 2
-- first the formula: |
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Nat.ModEq
import Mathlib.Data.Nat.Prime.Basic
import Mathlib.NumberTheory.Zsqrtd.Basic
/-!
# Pell's equation and Matiyasevic's theorem
This file solves Pell's equation, i.e. integer solutions to `x ^ 2 - d * y ^ 2 = 1`
*in the special case that `d = a ^ 2 - 1`*.
This is then applied to prove Matiyasevic's theorem that the power
function is Diophantine, which is the last key ingredient in the solution to Hilbert's tenth
problem. For the definition of Diophantine function, see `NumberTheory.Dioph`.
For results on Pell's equation for arbitrary (positive, non-square) `d`, see
`NumberTheory.Pell`.
## Main definition
* `pell` is a function assigning to a natural number `n` the `n`-th solution to Pell's equation
constructed recursively from the initial solution `(0, 1)`.
## Main statements
* `eq_pell` shows that every solution to Pell's equation is recursively obtained using `pell`
* `matiyasevic` shows that a certain system of Diophantine equations has a solution if and only if
the first variable is the `x`-component in a solution to Pell's equation - the key step towards
Hilbert's tenth problem in Davis' version of Matiyasevic's theorem.
* `eq_pow_of_pell` shows that the power function is Diophantine.
## Implementation notes
The proof of Matiyasevic's theorem doesn't follow Matiyasevic's original account of using Fibonacci
numbers but instead Davis' variant of using solutions to Pell's equation.
## References
* [M. Carneiro, _A Lean formalization of Matiyasevič's theorem_][carneiro2018matiyasevic]
* [M. Davis, _Hilbert's tenth problem is unsolvable_][MR317916]
## Tags
Pell's equation, Matiyasevic's theorem, Hilbert's tenth problem
-/
namespace Pell
open Nat
section
variable {d : ℤ}
/-- The property of being a solution to the Pell equation, expressed
as a property of elements of `ℤ√d`. -/
def IsPell : ℤ√d → Prop
| ⟨x, y⟩ => x * x - d * y * y = 1
theorem isPell_norm : ∀ {b : ℤ√d}, IsPell b ↔ b * star b = 1
| ⟨x, y⟩ => by simp [Zsqrtd.ext_iff, IsPell, mul_comm]; ring_nf
theorem isPell_iff_mem_unitary : ∀ {b : ℤ√d}, IsPell b ↔ b ∈ unitary (ℤ√d)
| ⟨x, y⟩ => by rw [unitary.mem_iff, isPell_norm, mul_comm (star _), and_self_iff]
theorem isPell_mul {b c : ℤ√d} (hb : IsPell b) (hc : IsPell c) : IsPell (b * c) :=
isPell_norm.2 (by simp [mul_comm, mul_left_comm c, mul_assoc,
star_mul, isPell_norm.1 hb, isPell_norm.1 hc])
theorem isPell_star : ∀ {b : ℤ√d}, IsPell b ↔ IsPell (star b)
| ⟨x, y⟩ => by simp [IsPell, Zsqrtd.star_mk]
end
section
variable {a : ℕ} (a1 : 1 < a)
private def d (_a1 : 1 < a) :=
a * a - 1
@[simp]
theorem d_pos : 0 < d a1 :=
tsub_pos_of_lt (mul_lt_mul a1 (le_of_lt a1) (by decide) (Nat.zero_le _) : 1 * 1 < a * a)
-- TODO(lint): Fix double namespace issue
/-- The Pell sequences, i.e. the sequence of integer solutions to `x ^ 2 - d * y ^ 2 = 1`, where
`d = a ^ 2 - 1`, defined together in mutual recursion. -/
--@[nolint dup_namespace]
def pell : ℕ → ℕ × ℕ
| 0 => (1, 0)
| n+1 => ((pell n).1 * a + d a1 * (pell n).2, (pell n).1 + (pell n).2 * a)
/-- The Pell `x` sequence. -/
def xn (n : ℕ) : ℕ :=
(pell a1 n).1
/-- The Pell `y` sequence. -/
def yn (n : ℕ) : ℕ :=
(pell a1 n).2
@[simp]
theorem pell_val (n : ℕ) : pell a1 n = (xn a1 n, yn a1 n) :=
show pell a1 n = ((pell a1 n).1, (pell a1 n).2) from
match pell a1 n with
| (_, _) => rfl
@[simp]
theorem xn_zero : xn a1 0 = 1 :=
rfl
@[simp]
theorem yn_zero : yn a1 0 = 0 :=
rfl
@[simp]
theorem xn_succ (n : ℕ) : xn a1 (n + 1) = xn a1 n * a + d a1 * yn a1 n :=
rfl
@[simp]
theorem yn_succ (n : ℕ) : yn a1 (n + 1) = xn a1 n + yn a1 n * a :=
rfl
theorem xn_one : xn a1 1 = a := by simp
theorem yn_one : yn a1 1 = 1 := by simp
/-- The Pell `x` sequence, considered as an integer sequence. -/
def xz (n : ℕ) : ℤ :=
xn a1 n
/-- The Pell `y` sequence, considered as an integer sequence. -/
def yz (n : ℕ) : ℤ :=
yn a1 n
section
/-- The element `a` such that `d = a ^ 2 - 1`, considered as an integer. -/
def az (a : ℕ) : ℤ :=
a
end
include a1 in
theorem asq_pos : 0 < a * a :=
le_trans (le_of_lt a1)
(by have := @Nat.mul_le_mul_left 1 a a (le_of_lt a1); rwa [mul_one] at this)
theorem dz_val : ↑(d a1) = az a * az a - 1 :=
have : 1 ≤ a * a := asq_pos a1
by rw [Pell.d, Int.ofNat_sub this]; rfl
@[simp]
theorem xz_succ (n : ℕ) : (xz a1 (n + 1)) = xz a1 n * az a + d a1 * yz a1 n :=
rfl
@[simp]
theorem yz_succ (n : ℕ) : yz a1 (n + 1) = xz a1 n + yz a1 n * az a :=
rfl
/-- The Pell sequence can also be viewed as an element of `ℤ√d` -/
def pellZd (n : ℕ) : ℤ√(d a1) :=
⟨xn a1 n, yn a1 n⟩
@[simp]
theorem pellZd_re (n : ℕ) : (pellZd a1 n).re = xn a1 n :=
rfl
@[simp]
theorem pellZd_im (n : ℕ) : (pellZd a1 n).im = yn a1 n :=
rfl
theorem isPell_nat {x y : ℕ} : IsPell (⟨x, y⟩ : ℤ√(d a1)) ↔ x * x - d a1 * y * y = 1 :=
⟨fun h =>
(Nat.cast_inj (R := ℤ)).1
(by rw [Int.ofNat_sub (Int.le_of_ofNat_le_ofNat <| Int.le.intro_sub _ h)]; exact h),
fun h =>
show ((x * x : ℕ) - (d a1 * y * y : ℕ) : ℤ) = 1 by
rw [← Int.ofNat_sub <| le_of_lt <| Nat.lt_of_sub_eq_succ h, h]; rfl⟩
@[simp]
theorem pellZd_succ (n : ℕ) : pellZd a1 (n + 1) = pellZd a1 n * ⟨a, 1⟩ := by ext <;> simp
theorem isPell_one : IsPell (⟨a, 1⟩ : ℤ√(d a1)) :=
show az a * az a - d a1 * 1 * 1 = 1 by simp [dz_val]
theorem isPell_pellZd : ∀ n : ℕ, IsPell (pellZd a1 n)
| 0 => rfl
| n + 1 => by
let o := isPell_one a1
simpa using Pell.isPell_mul (isPell_pellZd n) o
@[simp]
theorem pell_eqz (n : ℕ) : xz a1 n * xz a1 n - d a1 * yz a1 n * yz a1 n = 1 :=
isPell_pellZd a1 n
@[simp]
theorem pell_eq (n : ℕ) : xn a1 n * xn a1 n - d a1 * yn a1 n * yn a1 n = 1 :=
let pn := pell_eqz a1 n
have h : (↑(xn a1 n * xn a1 n) : ℤ) - ↑(d a1 * yn a1 n * yn a1 n) = 1 := by
repeat' rw [Int.natCast_mul]; exact pn
have hl : d a1 * yn a1 n * yn a1 n ≤ xn a1 n * xn a1 n :=
Nat.cast_le.1 <| Int.le.intro _ <| add_eq_of_eq_sub' <| Eq.symm h
(Nat.cast_inj (R := ℤ)).1 (by rw [Int.ofNat_sub hl]; exact h)
instance dnsq : Zsqrtd.Nonsquare (d a1) :=
⟨fun n h =>
have : n * n + 1 = a * a := by rw [← h]; exact Nat.succ_pred_eq_of_pos (asq_pos a1)
have na : n < a := Nat.mul_self_lt_mul_self_iff.1 (by rw [← this]; exact Nat.lt_succ_self _)
have : (n + 1) * (n + 1) ≤ n * n + 1 := by rw [this]; exact Nat.mul_self_le_mul_self na
have : n + n ≤ 0 :=
@Nat.le_of_add_le_add_right _ (n * n + 1) _ (by ring_nf at this ⊢; assumption)
Nat.ne_of_gt (d_pos a1) <| by
rwa [Nat.eq_zero_of_le_zero ((Nat.le_add_left _ _).trans this)] at h⟩
theorem xn_ge_a_pow : ∀ n : ℕ, a ^ n ≤ xn a1 n
| 0 => le_refl 1
| n + 1 => by
simp only [_root_.pow_succ, xn_succ]
exact le_trans (Nat.mul_le_mul_right _ (xn_ge_a_pow n)) (Nat.le_add_right _ _)
theorem n_lt_xn (n) : n < xn a1 n :=
lt_of_lt_of_le (Nat.lt_pow_self a1) (xn_ge_a_pow a1 n)
theorem x_pos (n) : 0 < xn a1 n :=
lt_of_le_of_lt (Nat.zero_le n) (n_lt_xn a1 n)
theorem eq_pell_lem : ∀ (n) (b : ℤ√(d a1)), 1 ≤ b → IsPell b →
b ≤ pellZd a1 n → ∃ n, b = pellZd a1 n
| 0, _ => fun h1 _ hl => ⟨0, @Zsqrtd.le_antisymm _ (dnsq a1) _ _ hl h1⟩
| n + 1, b => fun h1 hp h =>
have a1p : (0 : ℤ√(d a1)) ≤ ⟨a, 1⟩ := trivial
have am1p : (0 : ℤ√(d a1)) ≤ ⟨a, -1⟩ := show (_ : Nat) ≤ _ by simp; exact Nat.pred_le _
have a1m : (⟨a, 1⟩ * ⟨a, -1⟩ : ℤ√(d a1)) = 1 := isPell_norm.1 (isPell_one a1)
if ha : (⟨↑a, 1⟩ : ℤ√(d a1)) ≤ b then
let ⟨m, e⟩ :=
eq_pell_lem n (b * ⟨a, -1⟩) (by rw [← a1m]; exact mul_le_mul_of_nonneg_right ha am1p)
(isPell_mul hp (isPell_star.1 (isPell_one a1)))
(by
have t := mul_le_mul_of_nonneg_right h am1p
rwa [pellZd_succ, mul_assoc, a1m, mul_one] at t)
⟨m + 1, by
rw [show b = b * ⟨a, -1⟩ * ⟨a, 1⟩ by rw [mul_assoc, Eq.trans (mul_comm _ _) a1m]; simp,
pellZd_succ, e]⟩
else
suffices ¬1 < b from ⟨0, show b = 1 from (Or.resolve_left (lt_or_eq_of_le h1) this).symm⟩
fun h1l => by
obtain ⟨x, y⟩ := b
exact by
have bm : (_ * ⟨_, _⟩ : ℤ√d a1) = 1 := Pell.isPell_norm.1 hp
have y0l : (0 : ℤ√d a1) < ⟨x - x, y - -y⟩ :=
sub_lt_sub h1l fun hn : (1 : ℤ√d a1) ≤ ⟨x, -y⟩ => by
have t := mul_le_mul_of_nonneg_left hn (le_trans zero_le_one h1)
rw [bm, mul_one] at t
exact h1l t
have yl2 : (⟨_, _⟩ : ℤ√_) < ⟨_, _⟩ :=
show (⟨x, y⟩ - ⟨x, -y⟩ : ℤ√d a1) < ⟨a, 1⟩ - ⟨a, -1⟩ from
sub_lt_sub ha fun hn : (⟨x, -y⟩ : ℤ√d a1) ≤ ⟨a, -1⟩ => by
have t := mul_le_mul_of_nonneg_right
(mul_le_mul_of_nonneg_left hn (le_trans zero_le_one h1)) a1p
rw [bm, one_mul, mul_assoc, Eq.trans (mul_comm _ _) a1m, mul_one] at t
exact ha t
simp only [sub_self, sub_neg_eq_add] at y0l; simp only [Zsqrtd.neg_re, add_neg_cancel,
Zsqrtd.neg_im, neg_neg] at yl2
exact
match y, y0l, (yl2 : (⟨_, _⟩ : ℤ√_) < ⟨_, _⟩) with
| 0, y0l, _ => y0l (le_refl 0)
| (y + 1 : ℕ), _, yl2 =>
yl2
(Zsqrtd.le_of_le_le (by simp [sub_eq_add_neg])
(let t := Int.ofNat_le_ofNat_of_le (Nat.succ_pos y)
add_le_add t t))
| Int.negSucc _, y0l, _ => y0l trivial
theorem eq_pellZd (b : ℤ√(d a1)) (b1 : 1 ≤ b) (hp : IsPell b) : ∃ n, b = pellZd a1 n :=
let ⟨n, h⟩ := @Zsqrtd.le_arch (d a1) b
eq_pell_lem a1 n b b1 hp <|
h.trans <| by
rw [Zsqrtd.natCast_val]
exact
Zsqrtd.le_of_le_le (Int.ofNat_le_ofNat_of_le <| le_of_lt <| n_lt_xn _ _)
(Int.ofNat_zero_le _)
/-- Every solution to **Pell's equation** is recursively obtained from the initial solution
`(1,0)` using the recursion `pell`. -/
theorem eq_pell {x y : ℕ} (hp : x * x - d a1 * y * y = 1) : ∃ n, x = xn a1 n ∧ y = yn a1 n :=
have : (1 : ℤ√(d a1)) ≤ ⟨x, y⟩ :=
match x, hp with
| 0, (hp : 0 - _ = 1) => by rw [zero_tsub] at hp; contradiction
| x + 1, _hp =>
Zsqrtd.le_of_le_le (Int.ofNat_le_ofNat_of_le <| Nat.succ_pos x) (Int.ofNat_zero_le _)
let ⟨m, e⟩ := eq_pellZd a1 ⟨x, y⟩ this ((isPell_nat a1).2 hp)
⟨m,
match x, y, e with
| _, _, rfl => ⟨rfl, rfl⟩⟩
theorem pellZd_add (m) : ∀ n, pellZd a1 (m + n) = pellZd a1 m * pellZd a1 n
| 0 => (mul_one _).symm
| n + 1 => by rw [← add_assoc, pellZd_succ, pellZd_succ, pellZd_add _ n, ← mul_assoc]
theorem xn_add (m n) : xn a1 (m + n) = xn a1 m * xn a1 n + d a1 * yn a1 m * yn a1 n := by
injection pellZd_add a1 m n with h _
zify
rw [h]
simp [pellZd]
theorem yn_add (m n) : yn a1 (m + n) = xn a1 m * yn a1 n + yn a1 m * xn a1 n := by
injection pellZd_add a1 m n with _ h
zify
rw [h]
simp [pellZd]
theorem pellZd_sub {m n} (h : n ≤ m) : pellZd a1 (m - n) = pellZd a1 m * star (pellZd a1 n) := by
let t := pellZd_add a1 n (m - n)
rw [add_tsub_cancel_of_le h] at t
rw [t, mul_comm (pellZd _ n) _, mul_assoc, isPell_norm.1 (isPell_pellZd _ _), mul_one]
theorem xz_sub {m n} (h : n ≤ m) :
xz a1 (m - n) = xz a1 m * xz a1 n - d a1 * yz a1 m * yz a1 n := by
rw [sub_eq_add_neg, ← mul_neg]
exact congr_arg Zsqrtd.re (pellZd_sub a1 h)
theorem yz_sub {m n} (h : n ≤ m) : yz a1 (m - n) = xz a1 n * yz a1 m - xz a1 m * yz a1 n := by
rw [sub_eq_add_neg, ← mul_neg, mul_comm, add_comm]
exact congr_arg Zsqrtd.im (pellZd_sub a1 h)
theorem xy_coprime (n) : (xn a1 n).Coprime (yn a1 n) :=
Nat.coprime_of_dvd' fun k _ kx ky => by
let p := pell_eq a1 n
rw [← p]
exact Nat.dvd_sub (kx.mul_left _) (ky.mul_left _)
theorem strictMono_y : StrictMono (yn a1)
| _, 0, h => absurd h <| Nat.not_lt_zero _
| m, n + 1, h => by
have : yn a1 m ≤ yn a1 n :=
Or.elim (lt_or_eq_of_le <| Nat.le_of_succ_le_succ h) (fun hl => le_of_lt <| strictMono_y hl)
fun e => by rw [e]
simp only [yn_succ, gt_iff_lt]; refine lt_of_le_of_lt ?_ (Nat.lt_add_of_pos_left <| x_pos a1 n)
rw [← mul_one (yn a1 m)]
exact mul_le_mul this (le_of_lt a1) (Nat.zero_le _) (Nat.zero_le _)
theorem strictMono_x : StrictMono (xn a1)
| _, 0, h => absurd h <| Nat.not_lt_zero _
| m, n + 1, h => by
have : xn a1 m ≤ xn a1 n :=
Or.elim (lt_or_eq_of_le <| Nat.le_of_succ_le_succ h) (fun hl => le_of_lt <| strictMono_x hl)
fun e => by rw [e]
simp only [xn_succ, gt_iff_lt]
refine lt_of_lt_of_le (lt_of_le_of_lt this ?_) (Nat.le_add_right _ _)
have t := Nat.mul_lt_mul_of_pos_left a1 (x_pos a1 n)
rwa [mul_one] at t
theorem yn_ge_n : ∀ n, n ≤ yn a1 n
| 0 => Nat.zero_le _
| n + 1 =>
show n < yn a1 (n + 1) from lt_of_le_of_lt (yn_ge_n n) (strictMono_y a1 <| Nat.lt_succ_self n)
theorem y_mul_dvd (n) : ∀ k, yn a1 n ∣ yn a1 (n * k)
| 0 => dvd_zero _
| k + 1 => by
rw [Nat.mul_succ, yn_add]; exact dvd_add (dvd_mul_left _ _) ((y_mul_dvd _ k).mul_right _)
theorem y_dvd_iff (m n) : yn a1 m ∣ yn a1 n ↔ m ∣ n :=
⟨fun h =>
Nat.dvd_of_mod_eq_zero <|
(Nat.eq_zero_or_pos _).resolve_right fun hp => by
have co : Nat.Coprime (yn a1 m) (xn a1 (m * (n / m))) :=
Nat.Coprime.symm <| (xy_coprime a1 _).coprime_dvd_right (y_mul_dvd a1 m (n / m))
have m0 : 0 < m :=
m.eq_zero_or_pos.resolve_left fun e => by
rw [e, Nat.mod_zero] at hp;rw [e] at h
exact _root_.ne_of_lt (strictMono_y a1 hp) (eq_zero_of_zero_dvd h).symm
rw [← Nat.mod_add_div n m, yn_add] at h
exact
not_le_of_gt (strictMono_y _ <| Nat.mod_lt n m0)
(Nat.le_of_dvd (strictMono_y _ hp) <|
co.dvd_of_dvd_mul_right <|
(Nat.dvd_add_iff_right <| (y_mul_dvd _ _ _).mul_left _).2 h),
fun ⟨k, e⟩ => by rw [e]; apply y_mul_dvd⟩
theorem xy_modEq_yn (n) :
∀ k, xn a1 (n * k) ≡ xn a1 n ^ k [MOD yn a1 n ^ 2] ∧ yn a1 (n * k) ≡
k * xn a1 n ^ (k - 1) * yn a1 n [MOD yn a1 n ^ 3]
| 0 => by constructor <;> simpa using Nat.ModEq.refl _
| k + 1 => by
let ⟨hx, hy⟩ := xy_modEq_yn n k
have L : xn a1 (n * k) * xn a1 n + d a1 * yn a1 (n * k) * yn a1 n ≡
xn a1 n ^ k * xn a1 n + 0 [MOD yn a1 n ^ 2] :=
(hx.mul_right _).add <|
modEq_zero_iff_dvd.2 <| by
rw [_root_.pow_succ]
exact
mul_dvd_mul_right
(dvd_mul_of_dvd_right
(modEq_zero_iff_dvd.1 <|
(hy.of_dvd <| by simp [_root_.pow_succ]).trans <|
modEq_zero_iff_dvd.2 <| by simp)
_) _
have R : xn a1 (n * k) * yn a1 n + yn a1 (n * k) * xn a1 n ≡
xn a1 n ^ k * yn a1 n + k * xn a1 n ^ k * yn a1 n [MOD yn a1 n ^ 3] :=
ModEq.add
(by
rw [_root_.pow_succ]
exact hx.mul_right' _) <| by
have : k * xn a1 n ^ (k - 1) * yn a1 n * xn a1 n = k * xn a1 n ^ k * yn a1 n := by
rcases k with - | k <;> simp [_root_.pow_succ]; ring_nf
rw [← this]
exact hy.mul_right _
rw [add_tsub_cancel_right, Nat.mul_succ, xn_add, yn_add, pow_succ (xn _ n), Nat.succ_mul,
add_comm (k * xn _ n ^ k) (xn _ n ^ k), right_distrib]
exact ⟨L, R⟩
theorem ysq_dvd_yy (n) : yn a1 n * yn a1 n ∣ yn a1 (n * yn a1 n) :=
modEq_zero_iff_dvd.1 <|
((xy_modEq_yn a1 n (yn a1 n)).right.of_dvd <| by simp [_root_.pow_succ]).trans
(modEq_zero_iff_dvd.2 <| by simp [mul_dvd_mul_left, mul_assoc])
theorem dvd_of_ysq_dvd {n t} (h : yn a1 n * yn a1 n ∣ yn a1 t) : yn a1 n ∣ t :=
have nt : n ∣ t := (y_dvd_iff a1 n t).1 <| dvd_of_mul_left_dvd h
n.eq_zero_or_pos.elim (fun n0 => by rwa [n0] at nt ⊢) fun n0l : 0 < n => by
let ⟨k, ke⟩ := nt
have : yn a1 n ∣ k * xn a1 n ^ (k - 1) :=
Nat.dvd_of_mul_dvd_mul_right (strictMono_y a1 n0l) <|
modEq_zero_iff_dvd.1 <| by
have xm := (xy_modEq_yn a1 n k).right; rw [← ke] at xm
exact (xm.of_dvd <| by simp [_root_.pow_succ]).symm.trans h.modEq_zero_nat
rw [ke]
exact dvd_mul_of_dvd_right (((xy_coprime _ _).pow_left _).symm.dvd_of_dvd_mul_right this) _
| Mathlib/NumberTheory/PellMatiyasevic.lean | 436 | 452 | theorem pellZd_succ_succ (n) :
pellZd a1 (n + 2) + pellZd a1 n = (2 * a : ℕ) * pellZd a1 (n + 1) := by | have : (1 : ℤ√(d a1)) + ⟨a, 1⟩ * ⟨a, 1⟩ = ⟨a, 1⟩ * (2 * a) := by
rw [Zsqrtd.natCast_val]
change (⟨_, _⟩ : ℤ√(d a1)) = ⟨_, _⟩
rw [dz_val]
dsimp [az]
ext <;> dsimp <;> ring_nf
simpa [mul_add, mul_comm, mul_left_comm, add_comm] using congr_arg (· * pellZd a1 n) this
theorem xy_succ_succ (n) :
xn a1 (n + 2) + xn a1 n =
2 * a * xn a1 (n + 1) ∧ yn a1 (n + 2) + yn a1 n = 2 * a * yn a1 (n + 1) := by
have := pellZd_succ_succ a1 n; unfold pellZd at this
rw [Zsqrtd.nsmul_val (2 * a : ℕ)] at this
injection this with h₁ h₂
constructor <;> apply Int.ofNat.inj <;> [simpa using h₁; simpa using h₂] |
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Analysis.Complex.CauchyIntegral
import Mathlib.Analysis.InnerProductSpace.Convex
import Mathlib.Analysis.NormedSpace.Extr
import Mathlib.Data.Complex.FiniteDimensional
import Mathlib.Topology.Order.ExtrClosure
/-!
# Maximum modulus principle
In this file we prove several versions of the maximum modulus principle. There are several
statements that can be called "the maximum modulus principle" for maps between normed complex
spaces. They differ by assumptions on the domain (any space, a nontrivial space, a finite
dimensional space), assumptions on the codomain (any space, a strictly convex space), and by
conclusion (either equality of norms or of the values of the function).
## Main results
### Theorems for any codomain
Consider a function `f : E → F` that is complex differentiable on a set `s`, is continuous on its
closure, and `‖f x‖` has a maximum on `s` at `c`. We prove the following theorems.
- `Complex.norm_eqOn_closedBall_of_isMaxOn`: if `s = Metric.ball c r`, then `‖f x‖ = ‖f c‖` for
any `x` from the corresponding closed ball;
- `Complex.norm_eq_norm_of_isMaxOn_of_ball_subset`: if `Metric.ball c (dist w c) ⊆ s`, then
`‖f w‖ = ‖f c‖`;
- `Complex.norm_eqOn_of_isPreconnected_of_isMaxOn`: if `U` is an open (pre)connected set, `f` is
complex differentiable on `U`, and `‖f x‖` has a maximum on `U` at `c ∈ U`, then `‖f x‖ = ‖f c‖`
for all `x ∈ U`;
- `Complex.norm_eqOn_closure_of_isPreconnected_of_isMaxOn`: if `s` is open and (pre)connected
and `c ∈ s`, then `‖f x‖ = ‖f c‖` for all `x ∈ closure s`;
- `Complex.norm_eventually_eq_of_isLocalMax`: if `f` is complex differentiable in a neighborhood
of `c` and `‖f x‖` has a local maximum at `c`, then `‖f x‖` is locally a constant in a
neighborhood of `c`.
### Theorems for a strictly convex codomain
If the codomain `F` is a strictly convex space, then in the lemmas from the previous section we can
prove `f w = f c` instead of `‖f w‖ = ‖f c‖`, see
`Complex.eqOn_of_isPreconnected_of_isMaxOn_norm`,
`Complex.eqOn_closure_of_isPreconnected_of_isMaxOn_norm`,
`Complex.eq_of_isMaxOn_of_ball_subset`, `Complex.eqOn_closedBall_of_isMaxOn_norm`, and
`Complex.eventually_eq_of_isLocalMax_norm`.
### Values on the frontier
Finally, we prove some corollaries that relate the (norm of the) values of a function on a set to
its values on the frontier of the set. All these lemmas assume that `E` is a nontrivial space. In
this section `f g : E → F` are functions that are complex differentiable on a bounded set `s` and
are continuous on its closure. We prove the following theorems.
- `Complex.exists_mem_frontier_isMaxOn_norm`: If `E` is a finite dimensional space and `s` is a
nonempty bounded set, then there exists a point `z ∈ frontier s` such that `(‖f ·‖)` takes it
maximum value on `closure s` at `z`.
- `Complex.norm_le_of_forall_mem_frontier_norm_le`: if `‖f z‖ ≤ C` for all `z ∈ frontier s`, then
`‖f z‖ ≤ C` for all `z ∈ s`; note that this theorem does not require `E` to be a finite
dimensional space.
- `Complex.eqOn_closure_of_eqOn_frontier`: if `f x = g x` on the frontier of `s`, then `f x = g x`
on `closure s`;
- `Complex.eqOn_of_eqOn_frontier`: if `f x = g x` on the frontier of `s`, then `f x = g x`
on `s`.
## Tags
maximum modulus principle, complex analysis
-/
open TopologicalSpace Metric Set Filter Asymptotics Function MeasureTheory AffineMap Bornology
open scoped Topology Filter NNReal Real
universe u v w
variable {E : Type u} [NormedAddCommGroup E] [NormedSpace ℂ E] {F : Type v} [NormedAddCommGroup F]
[NormedSpace ℂ F]
local postfix:100 "̂" => UniformSpace.Completion
namespace Complex
/-!
### Auxiliary lemmas
We split the proof into a series of lemmas. First we prove the principle for a function `f : ℂ → F`
with an additional assumption that `F` is a complete space, then drop unneeded assumptions one by
one.
The lemmas with names `*_auxₙ` are considered to be private and should not be used outside of this
file.
-/
theorem norm_max_aux₁ [CompleteSpace F] {f : ℂ → F} {z w : ℂ}
(hd : DiffContOnCl ℂ f (ball z (dist w z)))
(hz : IsMaxOn (norm ∘ f) (closedBall z (dist w z)) z) : ‖f w‖ = ‖f z‖ := by
-- Consider a circle of radius `r = dist w z`.
set r : ℝ := dist w z
have hw : w ∈ closedBall z r := mem_closedBall.2 le_rfl
-- Assume the converse. Since `‖f w‖ ≤ ‖f z‖`, we have `‖f w‖ < ‖f z‖`.
refine (isMaxOn_iff.1 hz _ hw).antisymm (not_lt.1 ?_)
rintro hw_lt : ‖f w‖ < ‖f z‖
have hr : 0 < r := dist_pos.2 (ne_of_apply_ne (norm ∘ f) hw_lt.ne)
-- Due to Cauchy integral formula, it suffices to prove the following inequality.
suffices ‖∮ ζ in C(z, r), (ζ - z)⁻¹ • f ζ‖ < 2 * π * ‖f z‖ by
refine this.ne ?_
have A : (∮ ζ in C(z, r), (ζ - z)⁻¹ • f ζ) = (2 * π * I : ℂ) • f z :=
hd.circleIntegral_sub_inv_smul (mem_ball_self hr)
simp [A, norm_smul, Real.pi_pos.le]
suffices ‖∮ ζ in C(z, r), (ζ - z)⁻¹ • f ζ‖ < 2 * π * r * (‖f z‖ / r) by
rwa [mul_assoc, mul_div_cancel₀ _ hr.ne'] at this
/- This inequality is true because `‖(ζ - z)⁻¹ • f ζ‖ ≤ ‖f z‖ / r` for all `ζ` on the circle and
this inequality is strict at `ζ = w`. -/
have hsub : sphere z r ⊆ closedBall z r := sphere_subset_closedBall
refine circleIntegral.norm_integral_lt_of_norm_le_const_of_lt hr ?_ ?_ ⟨w, rfl, ?_⟩
· show ContinuousOn (fun ζ : ℂ => (ζ - z)⁻¹ • f ζ) (sphere z r)
refine ((continuousOn_id.sub continuousOn_const).inv₀ ?_).smul (hd.continuousOn_ball.mono hsub)
exact fun ζ hζ => sub_ne_zero.2 (ne_of_mem_sphere hζ hr.ne')
· show ∀ ζ ∈ sphere z r, ‖(ζ - z)⁻¹ • f ζ‖ ≤ ‖f z‖ / r
rintro ζ (hζ : ‖ζ - z‖ = r)
rw [le_div_iff₀ hr, norm_smul, norm_inv, hζ, mul_comm, mul_inv_cancel_left₀ hr.ne']
exact hz (hsub hζ)
show ‖(w - z)⁻¹ • f w‖ < ‖f z‖ / r
rw [norm_smul, norm_inv, ← div_eq_inv_mul]
exact (div_lt_div_iff_of_pos_right hr).2 hw_lt
/-!
Now we drop the assumption `CompleteSpace F` by embedding `F` into its completion.
-/
theorem norm_max_aux₂ {f : ℂ → F} {z w : ℂ} (hd : DiffContOnCl ℂ f (ball z (dist w z)))
(hz : IsMaxOn (norm ∘ f) (closedBall z (dist w z)) z) : ‖f w‖ = ‖f z‖ := by
set e : F →L[ℂ] F̂ := UniformSpace.Completion.toComplL
have he : ∀ x, ‖e x‖ = ‖x‖ := UniformSpace.Completion.norm_coe
replace hz : IsMaxOn (norm ∘ e ∘ f) (closedBall z (dist w z)) z := by
simpa only [IsMaxOn, Function.comp_def, he] using hz
simpa only [he, Function.comp_def]
using norm_max_aux₁ (e.differentiable.comp_diffContOnCl hd) hz
/-!
Then we replace the assumption `IsMaxOn (norm ∘ f) (Metric.closedBall z r) z` with a seemingly
weaker assumption `IsMaxOn (norm ∘ f) (Metric.ball z r) z`.
-/
theorem norm_max_aux₃ {f : ℂ → F} {z w : ℂ} {r : ℝ} (hr : dist w z = r)
(hd : DiffContOnCl ℂ f (ball z r)) (hz : IsMaxOn (norm ∘ f) (ball z r) z) : ‖f w‖ = ‖f z‖ := by
subst r
rcases eq_or_ne w z with (rfl | hne); · rfl
rw [← dist_ne_zero] at hne
exact norm_max_aux₂ hd (closure_ball z hne ▸ hz.closure hd.continuousOn.norm)
/-!
### Maximum modulus principle for any codomain
If we do not assume that the codomain is a strictly convex space, then we can only claim that the
**norm** `‖f x‖` is locally constant.
-/
/-!
Finally, we generalize the theorem from a disk in `ℂ` to a closed ball in any normed space.
-/
/-- **Maximum modulus principle** on a closed ball: if `f : E → F` is continuous on a closed ball,
is complex differentiable on the corresponding open ball, and the norm `‖f w‖` takes its maximum
value on the open ball at its center, then the norm `‖f w‖` is constant on the closed ball. -/
theorem norm_eqOn_closedBall_of_isMaxOn {f : E → F} {z : E} {r : ℝ}
(hd : DiffContOnCl ℂ f (ball z r)) (hz : IsMaxOn (norm ∘ f) (ball z r) z) :
EqOn (norm ∘ f) (const E ‖f z‖) (closedBall z r) := by
intro w hw
rw [mem_closedBall, dist_comm] at hw
rcases eq_or_ne z w with (rfl | hne); · rfl
set e := (lineMap z w : ℂ → E)
have hde : Differentiable ℂ e := (differentiable_id.smul_const (w - z)).add_const z
suffices ‖(f ∘ e) (1 : ℂ)‖ = ‖(f ∘ e) (0 : ℂ)‖ by simpa [e]
have hr : dist (1 : ℂ) 0 = 1 := by simp
have hball : MapsTo e (ball 0 1) (ball z r) := by
refine ((lipschitzWith_lineMap z w).mapsTo_ball (mt nndist_eq_zero.1 hne) 0 1).mono
Subset.rfl ?_
simpa only [lineMap_apply_zero, mul_one, coe_nndist] using ball_subset_ball hw
exact norm_max_aux₃ hr (hd.comp hde.diffContOnCl hball)
(hz.comp_mapsTo hball (lineMap_apply_zero z w))
/-- **Maximum modulus principle**: if `f : E → F` is complex differentiable on a set `s`, the norm
of `f` takes it maximum on `s` at `z`, and `w` is a point such that the closed ball with center `z`
and radius `dist w z` is included in `s`, then `‖f w‖ = ‖f z‖`. -/
theorem norm_eq_norm_of_isMaxOn_of_ball_subset {f : E → F} {s : Set E} {z w : E}
(hd : DiffContOnCl ℂ f s) (hz : IsMaxOn (norm ∘ f) s z) (hsub : ball z (dist w z) ⊆ s) :
‖f w‖ = ‖f z‖ :=
norm_eqOn_closedBall_of_isMaxOn (hd.mono hsub) (hz.on_subset hsub) (mem_closedBall.2 le_rfl)
/-- **Maximum modulus principle**: if `f : E → F` is complex differentiable in a neighborhood of `c`
and the norm `‖f z‖` has a local maximum at `c`, then `‖f z‖` is locally constant in a neighborhood
of `c`. -/
theorem norm_eventually_eq_of_isLocalMax {f : E → F} {c : E}
(hd : ∀ᶠ z in 𝓝 c, DifferentiableAt ℂ f z) (hc : IsLocalMax (norm ∘ f) c) :
∀ᶠ y in 𝓝 c, ‖f y‖ = ‖f c‖ := by
rcases nhds_basis_closedBall.eventually_iff.1 (hd.and hc) with ⟨r, hr₀, hr⟩
exact nhds_basis_closedBall.eventually_iff.2
⟨r, hr₀, norm_eqOn_closedBall_of_isMaxOn (DifferentiableOn.diffContOnCl fun x hx =>
(hr <| closure_ball_subset_closedBall hx).1.differentiableWithinAt) fun x hx =>
(hr <| ball_subset_closedBall hx).2⟩
theorem isOpen_setOf_mem_nhds_and_isMaxOn_norm {f : E → F} {s : Set E}
(hd : DifferentiableOn ℂ f s) : IsOpen {z | s ∈ 𝓝 z ∧ IsMaxOn (norm ∘ f) s z} := by
refine isOpen_iff_mem_nhds.2 fun z hz => (eventually_eventually_nhds.2 hz.1).and ?_
replace hd : ∀ᶠ w in 𝓝 z, DifferentiableAt ℂ f w := hd.eventually_differentiableAt hz.1
exact (norm_eventually_eq_of_isLocalMax hd <| hz.2.isLocalMax hz.1).mono fun x hx y hy =>
le_trans (hz.2 hy).out hx.ge
/-- **Maximum modulus principle** on a connected set. Let `U` be a (pre)connected open set in a
complex normed space. Let `f : E → F` be a function that is complex differentiable on `U`. Suppose
that `‖f x‖` takes its maximum value on `U` at `c ∈ U`. Then `‖f x‖ = ‖f c‖` for all `x ∈ U`. -/
theorem norm_eqOn_of_isPreconnected_of_isMaxOn {f : E → F} {U : Set E} {c : E}
(hc : IsPreconnected U) (ho : IsOpen U) (hd : DifferentiableOn ℂ f U) (hcU : c ∈ U)
(hm : IsMaxOn (norm ∘ f) U c) : EqOn (norm ∘ f) (const E ‖f c‖) U := by
set V := U ∩ {z | IsMaxOn (norm ∘ f) U z}
have hV : ∀ x ∈ V, ‖f x‖ = ‖f c‖ := fun x hx => le_antisymm (hm hx.1) (hx.2 hcU)
suffices U ⊆ V from fun x hx => hV x (this hx)
have hVo : IsOpen V := by
simpa only [ho.mem_nhds_iff, setOf_and, setOf_mem_eq]
using isOpen_setOf_mem_nhds_and_isMaxOn_norm hd
have hVne : (U ∩ V).Nonempty := ⟨c, hcU, hcU, hm⟩
set W := U ∩ {z | ‖f z‖ ≠ ‖f c‖}
have hWo : IsOpen W := hd.continuousOn.norm.isOpen_inter_preimage ho isOpen_ne
have hdVW : Disjoint V W := disjoint_left.mpr fun x hxV hxW => hxW.2 (hV x hxV)
have hUVW : U ⊆ V ∪ W := fun x hx =>
(eq_or_ne ‖f x‖ ‖f c‖).imp (fun h => ⟨hx, fun y hy => (hm hy).out.trans_eq h.symm⟩)
(And.intro hx)
exact hc.subset_left_of_subset_union hVo hWo hdVW hUVW hVne
/-- **Maximum modulus principle** on a connected set. Let `U` be a (pre)connected open set in a
complex normed space. Let `f : E → F` be a function that is complex differentiable on `U` and is
continuous on its closure. Suppose that `‖f x‖` takes its maximum value on `U` at `c ∈ U`. Then
`‖f x‖ = ‖f c‖` for all `x ∈ closure U`. -/
theorem norm_eqOn_closure_of_isPreconnected_of_isMaxOn {f : E → F} {U : Set E} {c : E}
(hc : IsPreconnected U) (ho : IsOpen U) (hd : DiffContOnCl ℂ f U) (hcU : c ∈ U)
(hm : IsMaxOn (norm ∘ f) U c) : EqOn (norm ∘ f) (const E ‖f c‖) (closure U) :=
(norm_eqOn_of_isPreconnected_of_isMaxOn hc ho hd.differentiableOn hcU hm).of_subset_closure
hd.continuousOn.norm continuousOn_const subset_closure Subset.rfl
section StrictConvex
/-!
### The case of a strictly convex codomain
If the codomain `F` is a strictly convex space, then we can claim equalities like `f w = f z`
instead of `‖f w‖ = ‖f z‖`.
Instead of repeating the proof starting with lemmas about integrals, we apply a corresponding lemma
above twice: for `f` and for `(f · + f c)`. Then we have `‖f w‖ = ‖f z‖` and
`‖f w + f z‖ = ‖f z + f z‖`, thus `‖f w + f z‖ = ‖f w‖ + ‖f z‖`. This is only possible if
`f w = f z`, see `eq_of_norm_eq_of_norm_add_eq`.
-/
variable [StrictConvexSpace ℝ F]
/-- **Maximum modulus principle** on a connected set. Let `U` be a (pre)connected open set in a
complex normed space. Let `f : E → F` be a function that is complex differentiable on `U`. Suppose
that `‖f x‖` takes its maximum value on `U` at `c ∈ U`. Then `f x = f c` for all `x ∈ U`.
TODO: change assumption from `IsMaxOn` to `IsLocalMax`. -/
theorem eqOn_of_isPreconnected_of_isMaxOn_norm {f : E → F} {U : Set E} {c : E}
(hc : IsPreconnected U) (ho : IsOpen U) (hd : DifferentiableOn ℂ f U) (hcU : c ∈ U)
(hm : IsMaxOn (norm ∘ f) U c) : EqOn f (const E (f c)) U := fun x hx =>
have H₁ : ‖f x‖ = ‖f c‖ := norm_eqOn_of_isPreconnected_of_isMaxOn hc ho hd hcU hm hx
have H₂ : ‖f x + f c‖ = ‖f c + f c‖ :=
norm_eqOn_of_isPreconnected_of_isMaxOn hc ho (hd.add_const _) hcU hm.norm_add_self hx
eq_of_norm_eq_of_norm_add_eq H₁ <| by simp only [H₂, SameRay.rfl.norm_add, H₁, Function.const]
/-- **Maximum modulus principle** on a connected set. Let `U` be a (pre)connected open set in a
complex normed space. Let `f : E → F` be a function that is complex differentiable on `U` and is
continuous on its closure. Suppose that `‖f x‖` takes its maximum value on `U` at `c ∈ U`. Then
`f x = f c` for all `x ∈ closure U`. -/
theorem eqOn_closure_of_isPreconnected_of_isMaxOn_norm {f : E → F} {U : Set E} {c : E}
(hc : IsPreconnected U) (ho : IsOpen U) (hd : DiffContOnCl ℂ f U) (hcU : c ∈ U)
(hm : IsMaxOn (norm ∘ f) U c) : EqOn f (const E (f c)) (closure U) :=
(eqOn_of_isPreconnected_of_isMaxOn_norm hc ho hd.differentiableOn hcU hm).of_subset_closure
hd.continuousOn continuousOn_const subset_closure Subset.rfl
/-- **Maximum modulus principle**. Let `f : E → F` be a function between complex normed spaces.
Suppose that the codomain `F` is a strictly convex space, `f` is complex differentiable on a set
`s`, `f` is continuous on the closure of `s`, the norm of `f` takes it maximum on `s` at `z`, and
`w` is a point such that the closed ball with center `z` and radius `dist w z` is included in `s`,
then `f w = f z`. -/
theorem eq_of_isMaxOn_of_ball_subset {f : E → F} {s : Set E} {z w : E} (hd : DiffContOnCl ℂ f s)
(hz : IsMaxOn (norm ∘ f) s z) (hsub : ball z (dist w z) ⊆ s) : f w = f z :=
have H₁ : ‖f w‖ = ‖f z‖ := norm_eq_norm_of_isMaxOn_of_ball_subset hd hz hsub
have H₂ : ‖f w + f z‖ = ‖f z + f z‖ :=
norm_eq_norm_of_isMaxOn_of_ball_subset (hd.add_const _) hz.norm_add_self hsub
eq_of_norm_eq_of_norm_add_eq H₁ <| by simp only [H₂, SameRay.rfl.norm_add, H₁]
/-- **Maximum modulus principle** on a closed ball. Suppose that a function `f : E → F` from a
normed complex space to a strictly convex normed complex space has the following properties:
- it is continuous on a closed ball `Metric.closedBall z r`,
- it is complex differentiable on the corresponding open ball;
- the norm `‖f w‖` takes its maximum value on the open ball at its center.
Then `f` is a constant on the closed ball. -/
theorem eqOn_closedBall_of_isMaxOn_norm {f : E → F} {z : E} {r : ℝ}
(hd : DiffContOnCl ℂ f (ball z r)) (hz : IsMaxOn (norm ∘ f) (ball z r) z) :
EqOn f (const E (f z)) (closedBall z r) := fun _x hx =>
eq_of_isMaxOn_of_ball_subset hd hz <| ball_subset_ball hx
/-- If `f` is differentiable on the open unit ball `{z : ℂ | ‖z‖ < 1}`, and `‖f‖` attains a maximum
in this open ball, then `f` is constant. -/
lemma eq_const_of_exists_max {f : E → F} {b : ℝ} (h_an : DifferentiableOn ℂ f (ball 0 b))
{v : E} (hv : v ∈ ball 0 b) (hv_max : IsMaxOn (norm ∘ f) (ball 0 b) v) :
Set.EqOn f (Function.const E (f v)) (ball 0 b) :=
Complex.eqOn_of_isPreconnected_of_isMaxOn_norm (convex_ball 0 b).isPreconnected
isOpen_ball h_an hv hv_max
/-- If `f` is a function differentiable on the open unit ball, and there exists an `r < 1` such that
any value of `‖f‖` on the open ball is bounded above by some value on the closed ball of radius `r`,
then `f` is constant. -/
lemma eq_const_of_exists_le [ProperSpace E] {f : E → F} {r b : ℝ}
(h_an : DifferentiableOn ℂ f (ball 0 b)) (hr_nn : 0 ≤ r) (hr_lt : r < b)
(hr : ∀ z, z ∈ (ball 0 b) → ∃ w, w ∈ closedBall 0 r ∧ ‖f z‖ ≤ ‖f w‖) :
Set.EqOn f (Function.const E (f 0)) (ball 0 b) := by
obtain ⟨x, hx_mem, hx_max⟩ := isCompact_closedBall (0 : E) r |>.exists_isMaxOn
(nonempty_closedBall.mpr hr_nn)
(h_an.continuousOn.mono <| closedBall_subset_ball hr_lt).norm
suffices Set.EqOn f (Function.const E (f x)) (ball 0 b) by
rwa [this (mem_ball_self (hr_nn.trans_lt hr_lt))]
apply eq_const_of_exists_max h_an (closedBall_subset_ball hr_lt hx_mem) (fun z hz ↦ ?_)
obtain ⟨w, hw, hw'⟩ := hr z hz
exact hw'.trans (hx_max hw)
/-- **Maximum modulus principle**: if `f : E → F` is complex differentiable in a neighborhood of `c`
and the norm `‖f z‖` has a local maximum at `c`, then `f` is locally constant in a neighborhood
of `c`. -/
| Mathlib/Analysis/Complex/AbsMax.lean | 343 | 351 | theorem eventually_eq_of_isLocalMax_norm {f : E → F} {c : E}
(hd : ∀ᶠ z in 𝓝 c, DifferentiableAt ℂ f z) (hc : IsLocalMax (norm ∘ f) c) :
∀ᶠ y in 𝓝 c, f y = f c := by | rcases nhds_basis_closedBall.eventually_iff.1 (hd.and hc) with ⟨r, hr₀, hr⟩
exact nhds_basis_closedBall.eventually_iff.2
⟨r, hr₀, eqOn_closedBall_of_isMaxOn_norm (DifferentiableOn.diffContOnCl fun x hx =>
(hr <| closure_ball_subset_closedBall hx).1.differentiableWithinAt) fun x hx =>
(hr <| ball_subset_closedBall hx).2⟩ |
/-
Copyright (c) 2014 Parikshit Khanna. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Parikshit Khanna, Jeremy Avigad, Leonardo de Moura, Floris van Doorn, Mario Carneiro
-/
import Mathlib.Data.List.Lemmas
import Mathlib.Data.Nat.Factorial.Basic
import Mathlib.Data.List.Count
import Mathlib.Data.List.Duplicate
import Mathlib.Data.List.InsertIdx
import Mathlib.Data.List.Induction
import Batteries.Data.List.Perm
import Mathlib.Data.List.Perm.Basic
/-!
# Permutations of a list
In this file we prove properties about `List.Permutations`, a list of all permutations of a list. It
is defined in `Data.List.Defs`.
## Order of the permutations
Designed for performance, the order in which the permutations appear in `List.Permutations` is
rather intricate and not very amenable to induction. That's why we also provide `List.Permutations'`
as a less efficient but more straightforward way of listing permutations.
### `List.Permutations`
TODO. In the meantime, you can try decrypting the docstrings.
### `List.Permutations'`
The list of partitions is built by recursion. The permutations of `[]` are `[[]]`. Then, the
permutations of `a :: l` are obtained by taking all permutations of `l` in order and adding `a` in
all positions. Hence, to build `[0, 1, 2, 3].permutations'`, it does
* `[[]]`
* `[[3]]`
* `[[2, 3], [3, 2]]]`
* `[[1, 2, 3], [2, 1, 3], [2, 3, 1], [1, 3, 2], [3, 1, 2], [3, 2, 1]]`
* `[[0, 1, 2, 3], [1, 0, 2, 3], [1, 2, 0, 3], [1, 2, 3, 0],`
`[0, 2, 1, 3], [2, 0, 1, 3], [2, 1, 0, 3], [2, 1, 3, 0],`
`[0, 2, 3, 1], [2, 0, 3, 1], [2, 3, 0, 1], [2, 3, 1, 0],`
`[0, 1, 3, 2], [1, 0, 3, 2], [1, 3, 0, 2], [1, 3, 2, 0],`
`[0, 3, 1, 2], [3, 0, 1, 2], [3, 1, 0, 2], [3, 1, 2, 0],`
`[0, 3, 2, 1], [3, 0, 2, 1], [3, 2, 0, 1], [3, 2, 1, 0]]`
-/
-- Make sure we don't import algebra
assert_not_exists Monoid
open Nat Function
variable {α β : Type*}
namespace List
theorem permutationsAux2_fst (t : α) (ts : List α) (r : List β) :
∀ (ys : List α) (f : List α → β), (permutationsAux2 t ts r ys f).1 = ys ++ ts
| [], _ => rfl
| y :: ys, f => by simp [permutationsAux2, permutationsAux2_fst t _ _ ys]
@[simp]
theorem permutationsAux2_snd_nil (t : α) (ts : List α) (r : List β) (f : List α → β) :
(permutationsAux2 t ts r [] f).2 = r :=
rfl
@[simp]
theorem permutationsAux2_snd_cons (t : α) (ts : List α) (r : List β) (y : α) (ys : List α)
(f : List α → β) :
(permutationsAux2 t ts r (y :: ys) f).2 =
f (t :: y :: ys ++ ts) :: (permutationsAux2 t ts r ys fun x : List α => f (y :: x)).2 := by
simp [permutationsAux2, permutationsAux2_fst t _ _ ys]
/-- The `r` argument to `permutationsAux2` is the same as appending. -/
theorem permutationsAux2_append (t : α) (ts : List α) (r : List β) (ys : List α) (f : List α → β) :
(permutationsAux2 t ts nil ys f).2 ++ r = (permutationsAux2 t ts r ys f).2 := by
induction ys generalizing f <;> simp [*]
/-- The `ts` argument to `permutationsAux2` can be folded into the `f` argument. -/
theorem permutationsAux2_comp_append {t : α} {ts ys : List α} {r : List β} (f : List α → β) :
((permutationsAux2 t [] r ys) fun x => f (x ++ ts)).2 = (permutationsAux2 t ts r ys f).2 := by
induction' ys with ys_hd _ ys_ih generalizing f
· simp
· simp [ys_ih fun xs => f (ys_hd :: xs)]
theorem map_permutationsAux2' {α' β'} (g : α → α') (g' : β → β') (t : α) (ts ys : List α)
(r : List β) (f : List α → β) (f' : List α' → β') (H : ∀ a, g' (f a) = f' (map g a)) :
map g' (permutationsAux2 t ts r ys f).2 =
(permutationsAux2 (g t) (map g ts) (map g' r) (map g ys) f').2 := by
induction' ys with ys_hd _ ys_ih generalizing f f'
· simp
· simp only [map, permutationsAux2_snd_cons, cons_append, cons.injEq]
rw [ys_ih]
· refine ⟨?_, rfl⟩
simp only [← map_cons, ← map_append]; apply H
· intro a; apply H
/-- The `f` argument to `permutationsAux2` when `r = []` can be eliminated. -/
theorem map_permutationsAux2 (t : α) (ts : List α) (ys : List α) (f : List α → β) :
(permutationsAux2 t ts [] ys id).2.map f = (permutationsAux2 t ts [] ys f).2 := by
rw [map_permutationsAux2' id, map_id, map_id]
· rfl
simp
/-- An expository lemma to show how all of `ts`, `r`, and `f` can be eliminated from
`permutationsAux2`.
`(permutationsAux2 t [] [] ys id).2`, which appears on the RHS, is a list whose elements are
produced by inserting `t` into every non-terminal position of `ys` in order. As an example:
```lean
#eval permutationsAux2 1 [] [] [2, 3, 4] id
-- [[1, 2, 3, 4], [2, 1, 3, 4], [2, 3, 1, 4]]
```
-/
theorem permutationsAux2_snd_eq (t : α) (ts : List α) (r : List β) (ys : List α) (f : List α → β) :
(permutationsAux2 t ts r ys f).2 =
((permutationsAux2 t [] [] ys id).2.map fun x => f (x ++ ts)) ++ r := by
rw [← permutationsAux2_append, map_permutationsAux2, permutationsAux2_comp_append]
theorem map_map_permutationsAux2 {α'} (g : α → α') (t : α) (ts ys : List α) :
map (map g) (permutationsAux2 t ts [] ys id).2 =
(permutationsAux2 (g t) (map g ts) [] (map g ys) id).2 :=
map_permutationsAux2' _ _ _ _ _ _ _ _ fun _ => rfl
theorem map_map_permutations'Aux (f : α → β) (t : α) (ts : List α) :
map (map f) (permutations'Aux t ts) = permutations'Aux (f t) (map f ts) := by
induction' ts with a ts ih
· rfl
· simp only [permutations'Aux, map_cons, map_map, ← ih, cons.injEq, true_and, Function.comp_def]
theorem permutations'Aux_eq_permutationsAux2 (t : α) (ts : List α) :
permutations'Aux t ts = (permutationsAux2 t [] [ts ++ [t]] ts id).2 := by
induction' ts with a ts ih; · rfl
simp only [permutations'Aux, ih, cons_append, permutationsAux2_snd_cons, append_nil, id_eq,
cons.injEq, true_and]
simp +singlePass only [← permutationsAux2_append]
simp [map_permutationsAux2]
theorem mem_permutationsAux2 {t : α} {ts : List α} {ys : List α} {l l' : List α} :
l' ∈ (permutationsAux2 t ts [] ys (l ++ ·)).2 ↔
∃ l₁ l₂, l₂ ≠ [] ∧ ys = l₁ ++ l₂ ∧ l' = l ++ l₁ ++ t :: l₂ ++ ts := by
induction' ys with y ys ih generalizing l
· simp +contextual
rw [permutationsAux2_snd_cons,
show (fun x : List α => l ++ y :: x) = (l ++ [y] ++ ·) by funext _; simp, mem_cons, ih]
constructor
· rintro (rfl | ⟨l₁, l₂, l0, rfl, rfl⟩)
· exact ⟨[], y :: ys, by simp⟩
· exact ⟨y :: l₁, l₂, l0, by simp⟩
· rintro ⟨_ | ⟨y', l₁⟩, l₂, l0, ye, rfl⟩
· simp [ye]
· simp only [cons_append] at ye
rcases ye with ⟨rfl, rfl⟩
exact Or.inr ⟨l₁, l₂, l0, by simp⟩
theorem mem_permutationsAux2' {t : α} {ts : List α} {ys : List α} {l : List α} :
l ∈ (permutationsAux2 t ts [] ys id).2 ↔
∃ l₁ l₂, l₂ ≠ [] ∧ ys = l₁ ++ l₂ ∧ l = l₁ ++ t :: l₂ ++ ts := by
rw [show @id (List α) = ([] ++ ·) by funext _; rfl]; apply mem_permutationsAux2
theorem length_permutationsAux2 (t : α) (ts : List α) (ys : List α) (f : List α → β) :
length (permutationsAux2 t ts [] ys f).2 = length ys := by
induction ys generalizing f <;> simp [*]
theorem foldr_permutationsAux2 (t : α) (ts : List α) (r L : List (List α)) :
foldr (fun y r => (permutationsAux2 t ts r y id).2) r L =
(L.flatMap fun y => (permutationsAux2 t ts [] y id).2) ++ r := by
induction' L with l L ih
· rfl
· simp_rw [foldr_cons, ih, flatMap_cons, append_assoc, permutationsAux2_append]
theorem mem_foldr_permutationsAux2 {t : α} {ts : List α} {r L : List (List α)} {l' : List α} :
l' ∈ foldr (fun y r => (permutationsAux2 t ts r y id).2) r L ↔
l' ∈ r ∨ ∃ l₁ l₂, l₁ ++ l₂ ∈ L ∧ l₂ ≠ [] ∧ l' = l₁ ++ t :: l₂ ++ ts := by
have :
(∃ a : List α,
a ∈ L ∧ ∃ l₁ l₂ : List α, ¬l₂ = nil ∧ a = l₁ ++ l₂ ∧ l' = l₁ ++ t :: (l₂ ++ ts)) ↔
∃ l₁ l₂ : List α, ¬l₂ = nil ∧ l₁ ++ l₂ ∈ L ∧ l' = l₁ ++ t :: (l₂ ++ ts) :=
⟨fun ⟨_, aL, l₁, l₂, l0, e, h⟩ => ⟨l₁, l₂, l0, e ▸ aL, h⟩, fun ⟨l₁, l₂, l0, aL, h⟩ =>
⟨_, aL, l₁, l₂, l0, rfl, h⟩⟩
rw [foldr_permutationsAux2]
simp only [mem_permutationsAux2', ← this, or_comm, and_left_comm, mem_append, mem_flatMap,
append_assoc, cons_append, exists_prop]
theorem length_foldr_permutationsAux2 (t : α) (ts : List α) (r L : List (List α)) :
length (foldr (fun y r => (permutationsAux2 t ts r y id).2) r L) =
(map length L).sum + length r := by
simp [foldr_permutationsAux2, Function.comp_def, length_permutationsAux2, length_flatMap]
theorem length_foldr_permutationsAux2' (t : α) (ts : List α) (r L : List (List α)) (n)
(H : ∀ l ∈ L, length l = n) :
length (foldr (fun y r => (permutationsAux2 t ts r y id).2) r L) = n * length L + length r := by
rw [length_foldr_permutationsAux2, (_ : (map length L).sum = n * length L)]
induction' L with l L ih
· simp
have sum_map : (map length L).sum = n * length L := ih fun l m => H l (mem_cons_of_mem _ m)
have length_l : length l = n := H _ mem_cons_self
simp [sum_map, length_l, Nat.mul_add, Nat.add_comm, mul_succ]
@[simp]
theorem permutationsAux_nil (is : List α) : permutationsAux [] is = [] := by
rw [permutationsAux, permutationsAux.rec]
@[simp]
theorem permutationsAux_cons (t : α) (ts is : List α) :
permutationsAux (t :: ts) is =
foldr (fun y r => (permutationsAux2 t ts r y id).2) (permutationsAux ts (t :: is))
(permutations is) := by
rw [permutationsAux, permutationsAux.rec]; rfl
@[simp]
theorem permutations_nil : permutations ([] : List α) = [[]] := by
rw [permutations, permutationsAux_nil]
theorem map_permutationsAux (f : α → β) :
∀ ts is :
List α, map (map f) (permutationsAux ts is) = permutationsAux (map f ts) (map f is) := by
refine permutationsAux.rec (by simp) ?_
introv IH1 IH2; rw [map] at IH2
simp only [foldr_permutationsAux2, map_append, map, map_map_permutationsAux2, permutations,
flatMap_map, IH1, append_assoc, permutationsAux_cons, flatMap_cons, ← IH2, map_flatMap]
theorem map_permutations (f : α → β) (ts : List α) :
map (map f) (permutations ts) = permutations (map f ts) := by
rw [permutations, permutations, map, map_permutationsAux, map]
theorem map_permutations' (f : α → β) (ts : List α) :
map (map f) (permutations' ts) = permutations' (map f ts) := by
induction' ts with t ts ih <;>
[rfl; simp [← ih, map_flatMap, ← map_map_permutations'Aux, flatMap_map]]
theorem permutationsAux_append (is is' ts : List α) :
permutationsAux (is ++ ts) is' =
(permutationsAux is is').map (· ++ ts) ++ permutationsAux ts (is.reverse ++ is') := by
induction' is with t is ih generalizing is'; · simp
simp only [foldr_permutationsAux2, ih, map_flatMap, cons_append, permutationsAux_cons, map_append,
reverse_cons, append_assoc, singleton_append]
congr 2
funext _
rw [map_permutationsAux2]
simp +singlePass only [← permutationsAux2_comp_append]
simp only [id, append_assoc]
theorem permutations_append (is ts : List α) :
permutations (is ++ ts) = (permutations is).map (· ++ ts) ++ permutationsAux ts is.reverse := by
simp [permutations, permutationsAux_append]
theorem perm_of_mem_permutationsAux :
∀ {ts is l : List α}, l ∈ permutationsAux ts is → l ~ ts ++ is := by
show ∀ (ts is l : List α), l ∈ permutationsAux ts is → l ~ ts ++ is
refine permutationsAux.rec (by simp) ?_
introv IH1 IH2 m
rw [permutationsAux_cons, permutations, mem_foldr_permutationsAux2] at m
rcases m with (m | ⟨l₁, l₂, m, _, rfl⟩)
· exact (IH1 _ m).trans perm_middle
· have p : l₁ ++ l₂ ~ is := by
simp only [mem_cons] at m
rcases m with e | m
· simp [e]
exact is.append_nil ▸ IH2 _ m
exact ((perm_middle.trans (p.cons _)).append_right _).trans (perm_append_comm.cons _)
theorem perm_of_mem_permutations {l₁ l₂ : List α} (h : l₁ ∈ permutations l₂) : l₁ ~ l₂ :=
(eq_or_mem_of_mem_cons h).elim (fun e => e ▸ Perm.refl _) fun m =>
append_nil l₂ ▸ perm_of_mem_permutationsAux m
| Mathlib/Data/List/Permutation.lean | 267 | 269 | theorem length_permutationsAux :
∀ ts is : List α, length (permutationsAux ts is) + is.length ! = (length ts + length is)! := by | refine permutationsAux.rec (by simp) ?_ |
/-
Copyright (c) 2020 Alexander Bentkamp, Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, Sébastien Gouëzel, Eric Wieser
-/
import Mathlib.Algebra.Algebra.RestrictScalars
import Mathlib.Algebra.CharP.Invertible
import Mathlib.Data.Complex.Basic
import Mathlib.LinearAlgebra.Matrix.ToLin
import Mathlib.Data.Real.Star
import Mathlib.Data.ZMod.Defs
/-!
# Complex number as a vector space over `ℝ`
This file contains the following instances:
* Any `•`-structure (`SMul`, `MulAction`, `DistribMulAction`, `Module`, `Algebra`) on
`ℝ` imbues a corresponding structure on `ℂ`. This includes the statement that `ℂ` is an `ℝ`
algebra.
* any complex vector space is a real vector space;
* any finite dimensional complex vector space is a finite dimensional real vector space;
* the space of `ℝ`-linear maps from a real vector space to a complex vector space is a complex
vector space.
It also defines bundled versions of four standard maps (respectively, the real part, the imaginary
part, the embedding of `ℝ` in `ℂ`, and the complex conjugate):
* `Complex.reLm` (`ℝ`-linear map);
* `Complex.imLm` (`ℝ`-linear map);
* `Complex.ofRealAm` (`ℝ`-algebra (homo)morphism);
* `Complex.conjAe` (`ℝ`-algebra equivalence).
It also provides a universal property of the complex numbers `Complex.lift`, which constructs a
`ℂ →ₐ[ℝ] A` into any `ℝ`-algebra `A` given a square root of `-1`.
In addition, this file provides a decomposition into `realPart` and `imaginaryPart` for any
element of a `StarModule` over `ℂ`.
## Notation
* `ℜ` and `ℑ` for the `realPart` and `imaginaryPart`, respectively, in the locale
`ComplexStarModule`.
-/
assert_not_exists NNReal
namespace Complex
open ComplexConjugate
open scoped SMul
variable {R : Type*} {S : Type*}
attribute [local ext] Complex.ext
/- The priority of the following instances has been manually lowered, as when they don't apply
they lead Lean to a very costly path, and most often they don't apply (most actions on `ℂ` don't
come from actions on `ℝ`). See https://github.com/leanprover-community/mathlib4/pull/11980 -/
-- priority manually adjusted in https://github.com/leanprover-community/mathlib4/pull/11980
instance (priority := 90) [SMul R ℝ] [SMul S ℝ] [SMulCommClass R S ℝ] : SMulCommClass R S ℂ where
smul_comm r s x := by ext <;> simp [smul_re, smul_im, smul_comm]
-- priority manually adjusted in https://github.com/leanprover-community/mathlib4/pull/11980
instance (priority := 90) [SMul R S] [SMul R ℝ] [SMul S ℝ] [IsScalarTower R S ℝ] :
IsScalarTower R S ℂ where
smul_assoc r s x := by ext <;> simp [smul_re, smul_im, smul_assoc]
-- priority manually adjusted in https://github.com/leanprover-community/mathlib4/pull/11980
instance (priority := 90) [SMul R ℝ] [SMul Rᵐᵒᵖ ℝ] [IsCentralScalar R ℝ] :
IsCentralScalar R ℂ where
op_smul_eq_smul r x := by ext <;> simp [smul_re, smul_im, op_smul_eq_smul]
-- priority manually adjusted in https://github.com/leanprover-community/mathlib4/pull/11980
instance (priority := 90) mulAction [Monoid R] [MulAction R ℝ] : MulAction R ℂ where
one_smul x := by ext <;> simp [smul_re, smul_im, one_smul]
mul_smul r s x := by ext <;> simp [smul_re, smul_im, mul_smul]
-- priority manually adjusted in https://github.com/leanprover-community/mathlib4/pull/11980
instance (priority := 90) distribSMul [DistribSMul R ℝ] : DistribSMul R ℂ where
smul_add r x y := by ext <;> simp [smul_re, smul_im, smul_add]
smul_zero r := by ext <;> simp [smul_re, smul_im, smul_zero]
-- priority manually adjusted in https://github.com/leanprover-community/mathlib4/pull/11980
instance (priority := 90) [Semiring R] [DistribMulAction R ℝ] : DistribMulAction R ℂ :=
{ Complex.distribSMul, Complex.mulAction with }
-- priority manually adjusted in https://github.com/leanprover-community/mathlib4/pull/11980
instance (priority := 100) instModule [Semiring R] [Module R ℝ] : Module R ℂ where
add_smul r s x := by ext <;> simp [smul_re, smul_im, add_smul]
zero_smul r := by ext <;> simp [smul_re, smul_im, zero_smul]
-- priority manually adjusted in https://github.com/leanprover-community/mathlib4/pull/11980
instance (priority := 95) instAlgebraOfReal [CommSemiring R] [Algebra R ℝ] : Algebra R ℂ where
algebraMap := Complex.ofRealHom.comp (algebraMap R ℝ)
smul := (· • ·)
smul_def' := fun r x => by ext <;> simp [smul_re, smul_im, Algebra.smul_def]
commutes' := fun r ⟨xr, xi⟩ => by ext <;> simp [smul_re, smul_im, Algebra.commutes]
instance : StarModule ℝ ℂ :=
⟨fun r x => by simp only [star_def, star_trivial, real_smul, map_mul, conj_ofReal]⟩
@[simp]
theorem coe_algebraMap : (algebraMap ℝ ℂ : ℝ → ℂ) = ((↑) : ℝ → ℂ) :=
rfl
section
variable {A : Type*} [Semiring A] [Algebra ℝ A]
/-- We need this lemma since `Complex.coe_algebraMap` diverts the simp-normal form away from
`AlgHom.commutes`. -/
@[simp]
theorem _root_.AlgHom.map_coe_real_complex (f : ℂ →ₐ[ℝ] A) (x : ℝ) : f x = algebraMap ℝ A x :=
f.commutes x
/-- Two `ℝ`-algebra homomorphisms from `ℂ` are equal if they agree on `Complex.I`. -/
@[ext]
theorem algHom_ext ⦃f g : ℂ →ₐ[ℝ] A⦄ (h : f I = g I) : f = g := by
ext ⟨x, y⟩
simp only [mk_eq_add_mul_I, map_add, AlgHom.map_coe_real_complex, map_mul, h]
end
open Submodule
/-- `ℂ` has a basis over `ℝ` given by `1` and `I`. -/
noncomputable def basisOneI : Basis (Fin 2) ℝ ℂ :=
Basis.ofEquivFun
{ toFun := fun z => ![z.re, z.im]
invFun := fun c => c 0 + c 1 • I
left_inv := fun z => by simp
right_inv := fun c => by
ext i
fin_cases i <;> simp
map_add' := fun z z' => by simp
map_smul' := fun c z => by simp }
@[simp]
theorem coe_basisOneI_repr (z : ℂ) : ⇑(basisOneI.repr z) = ![z.re, z.im] :=
rfl
@[simp]
theorem coe_basisOneI : ⇑basisOneI = ![1, I] :=
funext fun i =>
Basis.apply_eq_iff.mpr <|
Finsupp.ext fun j => by
fin_cases i <;> fin_cases j <;> simp
end Complex
/- Register as an instance (with low priority) the fact that a complex vector space is also a real
vector space. -/
instance (priority := 900) Module.complexToReal (E : Type*) [AddCommGroup E] [Module ℂ E] :
Module ℝ E :=
RestrictScalars.module ℝ ℂ E
/- Register as an instance (with low priority) the fact that a complex algebra is also a real
algebra. -/
instance (priority := 900) Algebra.complexToReal {A : Type*} [Semiring A] [Algebra ℂ A] :
Algebra ℝ A :=
RestrictScalars.algebra ℝ ℂ A
-- try to make sure we're not introducing diamonds but we will need
-- `reducible_and_instances` which currently fails https://github.com/leanprover-community/mathlib4/issues/10906
example : Prod.algebra ℝ ℂ ℂ = (Prod.algebra ℂ ℂ ℂ).complexToReal := rfl
-- try to make sure we're not introducing diamonds but we will need
-- `reducible_and_instances` which currently fails https://github.com/leanprover-community/mathlib4/issues/10906
example {ι : Type*} [Fintype ι] :
Pi.algebra (R := ℝ) ι (fun _ ↦ ℂ) = (Pi.algebra (R := ℂ) ι (fun _ ↦ ℂ)).complexToReal :=
rfl
example {A : Type*} [Ring A] [inst : Algebra ℂ A] :
(inst.complexToReal).toModule = (inst.toModule).complexToReal := by
with_reducible_and_instances rfl
@[simp, norm_cast]
theorem Complex.coe_smul {E : Type*} [AddCommGroup E] [Module ℂ E] (x : ℝ) (y : E) :
(x : ℂ) • y = x • y :=
rfl
/-- The scalar action of `ℝ` on a `ℂ`-module `E` induced by `Module.complexToReal` commutes with
another scalar action of `M` on `E` whenever the action of `ℂ` commutes with the action of `M`. -/
instance (priority := 900) SMulCommClass.complexToReal {M E : Type*} [AddCommGroup E] [Module ℂ E]
[SMul M E] [SMulCommClass ℂ M E] : SMulCommClass ℝ M E where
smul_comm r _ _ := smul_comm (r : ℂ) _ _
/-- The scalar action of `ℝ` on a `ℂ`-module `E` induced by `Module.complexToReal` associates with
another scalar action of `M` on `E` whenever the action of `ℂ` associates with the action of `M`. -/
instance IsScalarTower.complexToReal {M E : Type*} [AddCommGroup M] [Module ℂ M] [AddCommGroup E]
[Module ℂ E] [SMul M E] [IsScalarTower ℂ M E] : IsScalarTower ℝ M E where
smul_assoc r _ _ := smul_assoc (r : ℂ) _ _
-- check that the following instance is implied by the one above.
example (E : Type*) [AddCommGroup E] [Module ℂ E] : IsScalarTower ℝ ℂ E := inferInstance
instance (priority := 900) StarModule.complexToReal {E : Type*} [AddCommGroup E] [Star E]
[Module ℂ E] [StarModule ℂ E] : StarModule ℝ E :=
⟨fun r a => by rw [← smul_one_smul ℂ r a, star_smul, star_smul, star_one, smul_one_smul]⟩
namespace Complex
open ComplexConjugate
/-- Linear map version of the real part function, from `ℂ` to `ℝ`. -/
def reLm : ℂ →ₗ[ℝ] ℝ where
toFun x := x.re
map_add' := add_re
map_smul' := by simp
@[simp]
theorem reLm_coe : ⇑reLm = re :=
rfl
/-- Linear map version of the imaginary part function, from `ℂ` to `ℝ`. -/
def imLm : ℂ →ₗ[ℝ] ℝ where
toFun x := x.im
map_add' := add_im
map_smul' := by simp
@[simp]
theorem imLm_coe : ⇑imLm = im :=
rfl
/-- `ℝ`-algebra morphism version of the canonical embedding of `ℝ` in `ℂ`. -/
def ofRealAm : ℝ →ₐ[ℝ] ℂ :=
Algebra.ofId ℝ ℂ
@[simp]
theorem ofRealAm_coe : ⇑ofRealAm = ((↑) : ℝ → ℂ) :=
rfl
/-- `ℝ`-algebra isomorphism version of the complex conjugation function from `ℂ` to `ℂ` -/
def conjAe : ℂ ≃ₐ[ℝ] ℂ :=
{ conj with
invFun := conj
left_inv := star_star
right_inv := star_star
commutes' := conj_ofReal }
@[simp]
theorem conjAe_coe : ⇑conjAe = conj :=
rfl
/-- The matrix representation of `conjAe`. -/
@[simp]
theorem toMatrix_conjAe :
LinearMap.toMatrix basisOneI basisOneI conjAe.toLinearMap = !![1, 0; 0, -1] := by
ext i j
fin_cases i <;> fin_cases j <;> simp [LinearMap.toMatrix_apply]
/-- The identity and the complex conjugation are the only two `ℝ`-algebra homomorphisms of `ℂ`. -/
theorem real_algHom_eq_id_or_conj (f : ℂ →ₐ[ℝ] ℂ) : f = AlgHom.id ℝ ℂ ∨ f = conjAe := by
refine
(eq_or_eq_neg_of_sq_eq_sq (f I) I <| by rw [← map_pow, I_sq, map_neg, map_one]).imp ?_ ?_ <;>
refine fun h => algHom_ext ?_
exacts [h, conj_I.symm ▸ h]
/-- The natural `LinearEquiv` from `ℂ` to `ℝ × ℝ`. -/
@[simps! +simpRhs apply symm_apply_re symm_apply_im]
def equivRealProdLm : ℂ ≃ₗ[ℝ] ℝ × ℝ :=
{ equivRealProdAddHom with
map_smul' := fun r c => by simp }
theorem equivRealProdLm_symm_apply (p : ℝ × ℝ) :
Complex.equivRealProdLm.symm p = p.1 + p.2 * Complex.I := Complex.equivRealProd_symm_apply p
section lift
variable {A : Type*} [Ring A] [Algebra ℝ A]
/-- There is an alg_hom from `ℂ` to any `ℝ`-algebra with an element that squares to `-1`.
See `Complex.lift` for this as an equiv. -/
def liftAux (I' : A) (hf : I' * I' = -1) : ℂ →ₐ[ℝ] A :=
AlgHom.ofLinearMap
((Algebra.linearMap ℝ A).comp reLm + (LinearMap.toSpanSingleton _ _ I').comp imLm)
(show algebraMap ℝ A 1 + (0 : ℝ) • I' = 1 by rw [RingHom.map_one, zero_smul, add_zero])
fun ⟨x₁, y₁⟩ ⟨x₂, y₂⟩ =>
show
algebraMap ℝ A (x₁ * x₂ - y₁ * y₂) + (x₁ * y₂ + y₁ * x₂) • I' =
(algebraMap ℝ A x₁ + y₁ • I') * (algebraMap ℝ A x₂ + y₂ • I') by
rw [add_mul, mul_add, mul_add, add_comm _ (y₁ • I' * y₂ • I'), add_add_add_comm]
congr 1
-- equate "real" and "imaginary" parts
· rw [smul_mul_smul_comm, hf, smul_neg, ← Algebra.algebraMap_eq_smul_one, ← sub_eq_add_neg,
← RingHom.map_mul, ← RingHom.map_sub]
· rw [Algebra.smul_def, Algebra.smul_def, Algebra.smul_def, ← Algebra.right_comm _ x₂,
← mul_assoc, ← add_mul, ← RingHom.map_mul, ← RingHom.map_mul, ← RingHom.map_add]
@[simp]
theorem liftAux_apply (I' : A) (hI') (z : ℂ) : liftAux I' hI' z = algebraMap ℝ A z.re + z.im • I' :=
rfl
theorem liftAux_apply_I (I' : A) (hI') : liftAux I' hI' I = I' := by simp
/-- A universal property of the complex numbers, providing a unique `ℂ →ₐ[ℝ] A` for every element
of `A` which squares to `-1`.
This can be used to embed the complex numbers in the `Quaternion`s.
This isomorphism is named to match the very similar `Zsqrtd.lift`. -/
@[simps +simpRhs]
def lift : { I' : A // I' * I' = -1 } ≃ (ℂ →ₐ[ℝ] A) where
toFun I' := liftAux I' I'.prop
invFun F := ⟨F I, by rw [← map_mul, I_mul_I, map_neg, map_one]⟩
left_inv I' := Subtype.ext <| liftAux_apply_I (I' : A) I'.prop
right_inv _ := algHom_ext <| liftAux_apply_I _ _
-- When applied to `Complex.I` itself, `lift` is the identity.
@[simp]
theorem liftAux_I : liftAux I I_mul_I = AlgHom.id ℝ ℂ :=
algHom_ext <| liftAux_apply_I _ _
-- When applied to `-Complex.I`, `lift` is conjugation, `conj`.
@[simp]
theorem liftAux_neg_I : liftAux (-I) ((neg_mul_neg _ _).trans I_mul_I) = conjAe :=
algHom_ext <| (liftAux_apply_I _ _).trans conj_I.symm
end lift
end Complex
section RealImaginaryPart
open Complex
variable {A : Type*} [AddCommGroup A] [Module ℂ A] [StarAddMonoid A] [StarModule ℂ A]
/-- Create a `selfAdjoint` element from a `skewAdjoint` element by multiplying by the scalar
`-Complex.I`. -/
@[simps]
def skewAdjoint.negISMul : skewAdjoint A →ₗ[ℝ] selfAdjoint A where
toFun a :=
⟨-I • ↑a, by
simp only [neg_smul, neg_mem_iff, selfAdjoint.mem_iff, star_smul, star_def, conj_I,
star_val_eq, smul_neg, neg_neg]⟩
map_add' a b := by
ext
simp only [AddSubgroup.coe_add, smul_add, AddMemClass.mk_add_mk]
map_smul' a b := by
ext
simp only [neg_smul, skewAdjoint.val_smul, AddSubgroup.coe_mk, RingHom.id_apply,
selfAdjoint.val_smul, smul_neg, neg_inj]
rw [smul_comm]
theorem skewAdjoint.I_smul_neg_I (a : skewAdjoint A) : I • (skewAdjoint.negISMul a : A) = a := by
simp only [smul_smul, skewAdjoint.negISMul_apply_coe, neg_smul, smul_neg, I_mul_I, one_smul,
neg_neg]
/-- The real part `ℜ a` of an element `a` of a star module over `ℂ`, as a linear map. This is just
`selfAdjointPart ℝ`, but we provide it as a separate definition in order to link it with lemmas
concerning the `imaginaryPart`, which doesn't exist in star modules over other rings. -/
noncomputable def realPart : A →ₗ[ℝ] selfAdjoint A :=
selfAdjointPart ℝ
/-- The imaginary part `ℑ a` of an element `a` of a star module over `ℂ`, as a linear map into the
self adjoint elements. In a general star module, we have a decomposition into the `selfAdjoint`
and `skewAdjoint` parts, but in a star module over `ℂ` we have
`realPart_add_I_smul_imaginaryPart`, which allows us to decompose into a linear combination of
`selfAdjoint`s. -/
noncomputable def imaginaryPart : A →ₗ[ℝ] selfAdjoint A :=
skewAdjoint.negISMul.comp (skewAdjointPart ℝ)
@[inherit_doc]
scoped[ComplexStarModule] notation "ℜ" => realPart
@[inherit_doc]
scoped[ComplexStarModule] notation "ℑ" => imaginaryPart
open ComplexStarModule
theorem realPart_apply_coe (a : A) : (ℜ a : A) = (2 : ℝ)⁻¹ • (a + star a) := by
unfold realPart
simp only [selfAdjointPart_apply_coe, invOf_eq_inv]
theorem imaginaryPart_apply_coe (a : A) : (ℑ a : A) = -I • (2 : ℝ)⁻¹ • (a - star a) := by
unfold imaginaryPart
simp only [LinearMap.coe_comp, Function.comp_apply, skewAdjoint.negISMul_apply_coe,
skewAdjointPart_apply_coe, invOf_eq_inv, neg_smul]
/-- The standard decomposition of `ℜ a + Complex.I • ℑ a = a` of an element of a star module over
`ℂ` into a linear combination of self adjoint elements. -/
theorem realPart_add_I_smul_imaginaryPart (a : A) : (ℜ a : A) + I • (ℑ a : A) = a := by
simpa only [smul_smul, realPart_apply_coe, imaginaryPart_apply_coe, neg_smul, I_mul_I, one_smul,
neg_sub, add_add_sub_cancel, smul_sub, smul_add, neg_sub_neg, invOf_eq_inv] using
invOf_two_smul_add_invOf_two_smul ℝ a
@[simp]
theorem realPart_I_smul (a : A) : ℜ (I • a) = -ℑ a := by
ext
simp [realPart_apply_coe, imaginaryPart_apply_coe, smul_comm I, sub_eq_add_neg, add_comm]
@[simp]
| Mathlib/Data/Complex/Module.lean | 395 | 397 | theorem imaginaryPart_I_smul (a : A) : ℑ (I • a) = ℜ a := by | ext
simp [realPart_apply_coe, imaginaryPart_apply_coe, smul_comm I (2⁻¹ : ℝ), smul_smul I] |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Order.Filter.AtTopBot.Finset
import Mathlib.Topology.Algebra.InfiniteSum.Group
import Mathlib.Topology.Algebra.Star
/-!
# Topological sums and functorial constructions
Lemmas on the interaction of `tprod`, `tsum`, `HasProd`, `HasSum` etc with products, Sigma and Pi
types, `MulOpposite`, etc.
-/
noncomputable section
open Filter Finset Function
open scoped Topology
variable {α β γ : Type*}
/-! ## Product, Sigma and Pi types -/
section ProdDomain
variable [CommMonoid α] [TopologicalSpace α]
@[to_additive]
theorem hasProd_pi_single [DecidableEq β] (b : β) (a : α) : HasProd (Pi.mulSingle b a) a := by
convert hasProd_ite_eq b a
simp [Pi.mulSingle_apply]
@[to_additive (attr := simp)]
theorem tprod_pi_single [DecidableEq β] (b : β) (a : α) : ∏' b', Pi.mulSingle b a b' = a := by
rw [tprod_eq_mulSingle b]
· simp
· intro b' hb'; simp [hb']
@[to_additive tsum_setProd_singleton_left]
lemma tprod_setProd_singleton_left (b : β) (t : Set γ) (f : β × γ → α) :
(∏' x : {b} ×ˢ t, f x) = ∏' c : t, f (b, c) := by
rw [tprod_congr_set_coe _ Set.singleton_prod, tprod_image _ (Prod.mk_right_injective b).injOn]
@[to_additive tsum_setProd_singleton_right]
lemma tprod_setProd_singleton_right (s : Set β) (c : γ) (f : β × γ → α) :
(∏' x : s ×ˢ {c}, f x) = ∏' b : s, f (b, c) := by
rw [tprod_congr_set_coe _ Set.prod_singleton, tprod_image _ (Prod.mk_left_injective c).injOn]
@[to_additive Summable.prod_symm]
theorem Multipliable.prod_symm {f : β × γ → α} (hf : Multipliable f) :
Multipliable fun p : γ × β ↦ f p.swap :=
(Equiv.prodComm γ β).multipliable_iff.2 hf
end ProdDomain
section ProdCodomain
variable [CommMonoid α] [TopologicalSpace α] [CommMonoid γ] [TopologicalSpace γ]
@[to_additive HasSum.prodMk]
theorem HasProd.prodMk {f : β → α} {g : β → γ} {a : α} {b : γ} (hf : HasProd f a)
(hg : HasProd g b) : HasProd (fun x ↦ (⟨f x, g x⟩ : α × γ)) ⟨a, b⟩ := by
simp [HasProd, ← prod_mk_prod, Filter.Tendsto.prodMk_nhds hf hg]
@[deprecated (since := "2025-03-10")]
alias HasSum.prod_mk := HasSum.prodMk
@[to_additive existing HasSum.prodMk, deprecated (since := "2025-03-10")]
alias HasProd.prod_mk := HasProd.prodMk
end ProdCodomain
section ContinuousMul
variable [CommMonoid α] [TopologicalSpace α] [ContinuousMul α]
section Sum
@[to_additive]
lemma HasProd.sum {α β M : Type*} [CommMonoid M] [TopologicalSpace M] [ContinuousMul M]
{f : α ⊕ β → M} {a b : M}
(h₁ : HasProd (f ∘ Sum.inl) a) (h₂ : HasProd (f ∘ Sum.inr) b) : HasProd f (a * b) := by
have : Tendsto ((∏ b ∈ ·, f b) ∘ sumEquiv.symm) (atTop.map sumEquiv) (nhds (a * b)) := by
rw [Finset.sumEquiv.map_atTop, ← prod_atTop_atTop_eq]
convert (tendsto_mul.comp (nhds_prod_eq (x := a) (y := b) ▸ Tendsto.prodMap h₁ h₂))
ext s
simp
simpa [Tendsto, ← Filter.map_map] using this
@[to_additive "For the statement that `tsum` commutes with `Finset.sum`,
see `Summable.tsum_finsetSum`."]
protected lemma Multipliable.tprod_sum {α β M : Type*} [CommMonoid M] [TopologicalSpace M]
[ContinuousMul M] [T2Space M] {f : α ⊕ β → M} (h₁ : Multipliable (f ∘ .inl))
(h₂ : Multipliable (f ∘ .inr)) : ∏' i, f i = (∏' i, f (.inl i)) * (∏' i, f (.inr i)) :=
(h₁.hasProd.sum h₂.hasProd).tprod_eq
@[deprecated (since := "2025-04-12")] alias tsum_sum := Summable.tsum_sum
@[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_sum :=
Multipliable.tprod_sum
@[to_additive]
lemma Multipliable.sum {α β M : Type*} [CommMonoid M] [TopologicalSpace M] [ContinuousMul M]
(f : α ⊕ β → M) (h₁ : Multipliable (f ∘ Sum.inl)) (h₂ : Multipliable (f ∘ Sum.inr)) :
Multipliable f :=
⟨_, .sum h₁.hasProd h₂.hasProd⟩
end Sum
section RegularSpace
variable [RegularSpace α]
@[to_additive]
theorem HasProd.sigma {γ : β → Type*} {f : (Σ b : β, γ b) → α} {g : β → α} {a : α}
(ha : HasProd f a) (hf : ∀ b, HasProd (fun c ↦ f ⟨b, c⟩) (g b)) : HasProd g a := by
classical
refine (atTop_basis.tendsto_iff (closed_nhds_basis a)).mpr ?_
rintro s ⟨hs, hsc⟩
rcases mem_atTop_sets.mp (ha hs) with ⟨u, hu⟩
use u.image Sigma.fst, trivial
intro bs hbs
simp only [Set.mem_preimage, Finset.le_iff_subset] at hu
have : Tendsto (fun t : Finset (Σ b, γ b) ↦ ∏ p ∈ t with p.1 ∈ bs, f p) atTop
(𝓝 <| ∏ b ∈ bs, g b) := by
simp only [← sigma_preimage_mk, prod_sigma]
refine tendsto_finset_prod _ fun b _ ↦ ?_
change
Tendsto (fun t ↦ (fun t ↦ ∏ s ∈ t, f ⟨b, s⟩) (preimage t (Sigma.mk b) _)) atTop (𝓝 (g b))
exact (hf b).comp (tendsto_finset_preimage_atTop_atTop (sigma_mk_injective))
refine hsc.mem_of_tendsto this (eventually_atTop.2 ⟨u, fun t ht ↦ hu _ fun x hx ↦ ?_⟩)
exact mem_filter.2 ⟨ht hx, hbs <| mem_image_of_mem _ hx⟩
/-- If a function `f` on `β × γ` has product `a` and for each `b` the restriction of `f` to
`{b} × γ` has product `g b`, then the function `g` has product `a`. -/
@[to_additive HasSum.prod_fiberwise "If a series `f` on `β × γ` has sum `a` and for each `b` the
restriction of `f` to `{b} × γ` has sum `g b`, then the series `g` has sum `a`."]
theorem HasProd.prod_fiberwise {f : β × γ → α} {g : β → α} {a : α} (ha : HasProd f a)
(hf : ∀ b, HasProd (fun c ↦ f (b, c)) (g b)) : HasProd g a :=
HasProd.sigma ((Equiv.sigmaEquivProd β γ).hasProd_iff.2 ha) hf
@[to_additive]
theorem Multipliable.sigma' {γ : β → Type*} {f : (Σ b : β, γ b) → α} (ha : Multipliable f)
(hf : ∀ b, Multipliable fun c ↦ f ⟨b, c⟩) : Multipliable fun b ↦ ∏' c, f ⟨b, c⟩ :=
(ha.hasProd.sigma fun b ↦ (hf b).hasProd).multipliable
end RegularSpace
section T3Space
variable [T3Space α]
@[to_additive]
theorem HasProd.sigma_of_hasProd {γ : β → Type*} {f : (Σ b : β, γ b) → α} {g : β → α}
{a : α} (ha : HasProd g a) (hf : ∀ b, HasProd (fun c ↦ f ⟨b, c⟩) (g b)) (hf' : Multipliable f) :
HasProd f a := by simpa [(hf'.hasProd.sigma hf).unique ha] using hf'.hasProd
@[to_additive]
protected theorem Multipliable.tprod_sigma' {γ : β → Type*} {f : (Σ b : β, γ b) → α}
(h₁ : ∀ b, Multipliable fun c ↦ f ⟨b, c⟩) (h₂ : Multipliable f) :
∏' p, f p = ∏' (b) (c), f ⟨b, c⟩ :=
(h₂.hasProd.sigma fun b ↦ (h₁ b).hasProd).tprod_eq.symm
@[deprecated (since := "2025-04-12")] alias tsum_sigma' := Summable.tsum_sigma'
@[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_sigma' :=
Multipliable.tprod_sigma'
@[to_additive Summable.tsum_prod']
protected theorem Multipliable.tprod_prod' {f : β × γ → α} (h : Multipliable f)
(h₁ : ∀ b, Multipliable fun c ↦ f (b, c)) :
∏' p, f p = ∏' (b) (c), f (b, c) :=
(h.hasProd.prod_fiberwise fun b ↦ (h₁ b).hasProd).tprod_eq.symm
@[deprecated (since := "2025-04-12")] alias tsum_prod' := Summable.tsum_prod'
@[to_additive existing Summable.tsum_prod', deprecated (since := "2025-04-12")] alias tprod_prod' :=
Multipliable.tprod_prod'
@[to_additive Summable.tsum_prod_uncurry]
protected theorem Multipliable.tprod_prod_uncurry {f : β → γ → α}
(h : Multipliable (Function.uncurry f)) (h₁ : ∀ b, Multipliable fun c ↦ f b c) :
∏' p : β × γ, uncurry f p = ∏' (b) (c), f b c :=
(h.hasProd.prod_fiberwise fun b ↦ (h₁ b).hasProd).tprod_eq.symm
@[deprecated (since := "2025-04-12")] alias tsum_prod_uncurry :=
Summable.tsum_prod_uncurry
@[to_additive existing Summable.tsum_prod_uncurry, deprecated (since := "2025-04-12")] alias
tprod_prod_uncurry := Multipliable.tprod_prod_uncurry
@[to_additive]
protected theorem Multipliable.tprod_comm' {f : β → γ → α} (h : Multipliable (Function.uncurry f))
(h₁ : ∀ b, Multipliable (f b)) (h₂ : ∀ c, Multipliable fun b ↦ f b c) :
∏' (c) (b), f b c = ∏' (b) (c), f b c := by
rw [← h.tprod_prod_uncurry h₁, ← h.prod_symm.tprod_prod_uncurry h₂,
← (Equiv.prodComm γ β).tprod_eq (uncurry f)]
rfl
@[deprecated (since := "2025-04-12")] alias tsum_comm':= Summable.tsum_comm'
@[to_additive existing, deprecated (since := "2025-04-12")] alias
tprod_comm' := Multipliable.tprod_comm'
end T3Space
end ContinuousMul
section CompleteSpace
variable [CommGroup α] [UniformSpace α] [IsUniformGroup α]
@[to_additive]
theorem HasProd.of_sigma {γ : β → Type*} {f : (Σ b : β, γ b) → α} {g : β → α} {a : α}
(hf : ∀ b, HasProd (fun c ↦ f ⟨b, c⟩) (g b)) (hg : HasProd g a)
(h : CauchySeq (fun (s : Finset (Σ b : β, γ b)) ↦ ∏ i ∈ s, f i)) :
HasProd f a := by
classical
apply le_nhds_of_cauchy_adhp h
simp only [← mapClusterPt_def, mapClusterPt_iff_frequently, frequently_atTop, ge_iff_le,
le_eq_subset]
intro u hu s
rcases mem_nhds_iff.1 hu with ⟨v, vu, v_open, hv⟩
obtain ⟨t0, st0, ht0⟩ : ∃ t0, ∏ i ∈ t0, g i ∈ v ∧ s.image Sigma.fst ⊆ t0 := by
have A : ∀ᶠ t0 in (atTop : Filter (Finset β)), ∏ i ∈ t0, g i ∈ v := hg (v_open.mem_nhds hv)
exact (A.and (Ici_mem_atTop _)).exists
have L : Tendsto (fun t : Finset (Σ b, γ b) ↦ ∏ p ∈ t with p.1 ∈ t0, f p) atTop
(𝓝 <| ∏ b ∈ t0, g b) := by
simp only [← sigma_preimage_mk, prod_sigma]
refine tendsto_finset_prod _ fun b _ ↦ ?_
change
Tendsto (fun t ↦ (fun t ↦ ∏ s ∈ t, f ⟨b, s⟩) (preimage t (Sigma.mk b) _)) atTop (𝓝 (g b))
exact (hf b).comp (tendsto_finset_preimage_atTop_atTop (sigma_mk_injective))
have : ∃ t, ∏ p ∈ t with p.1 ∈ t0, f p ∈ v ∧ s ⊆ t :=
((Tendsto.eventually_mem L (v_open.mem_nhds st0)).and (Ici_mem_atTop _)).exists
obtain ⟨t, tv, st⟩ := this
refine ⟨{p ∈ t | p.1 ∈ t0}, fun x hx ↦ ?_, vu tv⟩
simpa only [mem_filter, st hx, true_and] using ht0 (mem_image_of_mem Sigma.fst hx)
variable [CompleteSpace α]
@[to_additive]
theorem Multipliable.sigma_factor {γ : β → Type*} {f : (Σ b : β, γ b) → α}
(ha : Multipliable f) (b : β) :
Multipliable fun c ↦ f ⟨b, c⟩ :=
ha.comp_injective sigma_mk_injective
@[to_additive]
theorem Multipliable.sigma {γ : β → Type*} {f : (Σ b : β, γ b) → α} (ha : Multipliable f) :
Multipliable fun b ↦ ∏' c, f ⟨b, c⟩ :=
ha.sigma' fun b ↦ ha.sigma_factor b
@[to_additive Summable.prod_factor]
theorem Multipliable.prod_factor {f : β × γ → α} (h : Multipliable f) (b : β) :
Multipliable fun c ↦ f (b, c) :=
h.comp_injective fun _ _ h ↦ (Prod.ext_iff.1 h).2
@[to_additive Summable.prod]
lemma Multipliable.prod {f : β × γ → α} (h : Multipliable f) :
Multipliable fun b ↦ ∏' c, f (b, c) :=
((Equiv.sigmaEquivProd β γ).multipliable_iff.mpr h).sigma
@[to_additive]
lemma HasProd.tprod_fiberwise [T2Space α] {f : β → α} {a : α} (hf : HasProd f a) (g : β → γ) :
HasProd (fun c : γ ↦ ∏' b : g ⁻¹' {c}, f b) a :=
(((Equiv.sigmaFiberEquiv g).hasProd_iff).mpr hf).sigma <|
fun _ ↦ ((hf.multipliable.subtype _).hasProd_iff).mpr rfl
section CompleteT0Space
variable [T0Space α]
@[to_additive]
protected theorem Multipliable.tprod_sigma {γ : β → Type*} {f : (Σ b : β, γ b) → α}
(ha : Multipliable f) : ∏' p, f p = ∏' (b) (c), f ⟨b, c⟩ :=
Multipliable.tprod_sigma' (fun b ↦ ha.sigma_factor b) ha
@[deprecated (since := "2025-04-12")] alias tsum_sigma := Summable.tsum_sigma
@[to_additive existing, deprecated (since := "2025-04-12")] alias
tprod_sigma := Multipliable.tprod_sigma
@[to_additive Summable.tsum_prod]
protected theorem Multipliable.tprod_prod {f : β × γ → α} (h : Multipliable f) :
∏' p, f p = ∏' (b) (c), f ⟨b, c⟩ :=
h.tprod_prod' h.prod_factor
@[deprecated (since := "2025-04-12")] alias tsum_prod := Summable.tsum_prod
@[to_additive existing tsum_prod, deprecated (since := "2025-04-12")]
alias tprod_prod := Multipliable.tprod_prod
@[to_additive]
protected theorem Multipliable.tprod_comm {f : β → γ → α} (h : Multipliable (Function.uncurry f)) :
∏' (c) (b), f b c = ∏' (b) (c), f b c :=
h.tprod_comm' h.prod_factor h.prod_symm.prod_factor
@[deprecated (since := "2025-04-12")] alias tsum_comm := Summable.tsum_comm
@[to_additive existing, deprecated (since := "2025-04-12")] alias tprod_comm :=
Multipliable.tprod_comm
end CompleteT0Space
end CompleteSpace
section Pi
variable {ι : Type*} {π : α → Type*} [∀ x, CommMonoid (π x)] [∀ x, TopologicalSpace (π x)]
@[to_additive]
theorem Pi.hasProd {f : ι → ∀ x, π x} {g : ∀ x, π x} :
HasProd f g ↔ ∀ x, HasProd (fun i ↦ f i x) (g x) := by
simp only [HasProd, tendsto_pi_nhds, prod_apply]
@[to_additive]
| Mathlib/Topology/Algebra/InfiniteSum/Constructions.lean | 314 | 315 | theorem Pi.multipliable {f : ι → ∀ x, π x} : Multipliable f ↔ ∀ x, Multipliable fun i ↦ f i x := by | simp only [Multipliable, Pi.hasProd, Classical.skolem] |
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jens Wagemaker, Aaron Anderson
-/
import Mathlib.Algebra.GCDMonoid.Basic
import Mathlib.Algebra.Order.Group.Unbundled.Int
import Mathlib.Algebra.Ring.Int.Units
import Mathlib.Data.Int.GCD
/-!
# ℕ and ℤ are normalized GCD monoids.
## Main statements
* ℕ is a `GCDMonoid`
* ℕ is a `NormalizedGCDMonoid`
* ℤ is a `NormalizationMonoid`
* ℤ is a `GCDMonoid`
* ℤ is a `NormalizedGCDMonoid`
## Tags
natural numbers, integers, normalization monoid, gcd monoid, greatest common divisor
-/
assert_not_exists OrderedCommMonoid
/-- `ℕ` is a gcd_monoid. -/
instance : GCDMonoid ℕ where
gcd := Nat.gcd
lcm := Nat.lcm
gcd_dvd_left := Nat.gcd_dvd_left
gcd_dvd_right := Nat.gcd_dvd_right
dvd_gcd := Nat.dvd_gcd
gcd_mul_lcm a b := by rw [Nat.gcd_mul_lcm]; rfl
lcm_zero_left := Nat.lcm_zero_left
lcm_zero_right := Nat.lcm_zero_right
theorem gcd_eq_nat_gcd (m n : ℕ) : gcd m n = Nat.gcd m n :=
rfl
theorem lcm_eq_nat_lcm (m n : ℕ) : lcm m n = Nat.lcm m n :=
rfl
instance : NormalizedGCDMonoid ℕ :=
{ (inferInstance : GCDMonoid ℕ),
(inferInstance : NormalizationMonoid ℕ) with
normalize_gcd := fun _ _ => normalize_eq _
normalize_lcm := fun _ _ => normalize_eq _ }
namespace Int
section NormalizationMonoid
instance normalizationMonoid : NormalizationMonoid ℤ where
normUnit a := if 0 ≤ a then 1 else -1
normUnit_zero := if_pos le_rfl
normUnit_mul {a b} hna hnb := by
rcases hna.lt_or_lt with ha | ha <;> rcases hnb.lt_or_lt with hb | hb <;>
simp [Int.mul_nonneg_iff, ha.le, ha.not_le, hb.le, hb.not_le]
normUnit_coe_units u :=
(units_eq_one_or u).elim (fun eq => eq.symm ▸ if_pos Int.one_nonneg) fun eq =>
eq.symm ▸ if_neg (not_le_of_gt <| show (-1 : ℤ) < 0 by decide)
theorem normUnit_eq (z : ℤ) : normUnit z = if 0 ≤ z then 1 else -1 := rfl
| Mathlib/Algebra/GCDMonoid/Nat.lean | 67 | 68 | theorem normalize_of_nonneg {z : ℤ} (h : 0 ≤ z) : normalize z = z := by | rw [normalize_apply, normUnit_eq, if_pos h, Units.val_one, mul_one] |
/-
Copyright (c) 2024 Moritz Doll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Moritz Doll
-/
import Mathlib.Topology.ContinuousMap.ZeroAtInfty
/-!
# ZeroAtInftyContinuousMapClass in normed additive groups
In this file we give a characterization of the predicate `zero_at_infty` from
`ZeroAtInftyContinuousMapClass`. A continuous map `f` is zero at infinity if and only if
for every `ε > 0` there exists a `r : ℝ` such that for all `x : E` with `r < ‖x‖` it holds that
`‖f x‖ < ε`.
-/
open Topology Filter
variable {E F 𝓕 : Type*}
variable [SeminormedAddGroup E] [SeminormedAddCommGroup F]
variable [FunLike 𝓕 E F] [ZeroAtInftyContinuousMapClass 𝓕 E F]
theorem ZeroAtInftyContinuousMapClass.norm_le (f : 𝓕) (ε : ℝ) (hε : 0 < ε) :
∃ (r : ℝ), ∀ (x : E) (_hx : r < ‖x‖), ‖f x‖ < ε := by
have h := zero_at_infty f
rw [tendsto_zero_iff_norm_tendsto_zero, tendsto_def] at h
specialize h (Metric.ball 0 ε) (Metric.ball_mem_nhds 0 hε)
rcases Metric.closedBall_compl_subset_of_mem_cocompact h 0 with ⟨r, hr⟩
use r
intro x hr'
suffices x ∈ (fun x ↦ ‖f x‖) ⁻¹' Metric.ball 0 ε by aesop
apply hr
aesop
variable [ProperSpace E]
| Mathlib/Analysis/Normed/Group/ZeroAtInfty.lean | 38 | 49 | theorem zero_at_infty_of_norm_le (f : E → F)
(h : ∀ (ε : ℝ) (_hε : 0 < ε), ∃ (r : ℝ), ∀ (x : E) (_hx : r < ‖x‖), ‖f x‖ < ε) :
Tendsto f (cocompact E) (𝓝 0) := by | rw [tendsto_zero_iff_norm_tendsto_zero]
intro s hs
rw [mem_map, Metric.mem_cocompact_iff_closedBall_compl_subset 0]
rw [Metric.mem_nhds_iff] at hs
rcases hs with ⟨ε, hε, hs⟩
rcases h ε hε with ⟨r, hr⟩
use r
intro
aesop |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.MeasureTheory.MeasurableSpace.MeasurablyGenerated
import Mathlib.MeasureTheory.Measure.NullMeasurable
import Mathlib.Order.Interval.Set.Monotone
/-!
# Measure spaces
The definition of a measure and a measure space are in `MeasureTheory.MeasureSpaceDef`, with
only a few basic properties. This file provides many more properties of these objects.
This separation allows the measurability tactic to import only the file `MeasureSpaceDef`, and to
be available in `MeasureSpace` (through `MeasurableSpace`).
Given a measurable space `α`, a measure on `α` is a function that sends measurable sets to the
extended nonnegative reals that satisfies the following conditions:
1. `μ ∅ = 0`;
2. `μ` is countably additive. This means that the measure of a countable union of pairwise disjoint
sets is equal to the measure of the individual sets.
Every measure can be canonically extended to an outer measure, so that it assigns values to
all subsets, not just the measurable subsets. On the other hand, a measure that is countably
additive on measurable sets can be restricted to measurable sets to obtain a measure.
In this file a measure is defined to be an outer measure that is countably additive on
measurable sets, with the additional assumption that the outer measure is the canonical
extension of the restricted measure.
Measures on `α` form a complete lattice, and are closed under scalar multiplication with `ℝ≥0∞`.
Given a measure, the null sets are the sets where `μ s = 0`, where `μ` denotes the corresponding
outer measure (so `s` might not be measurable). We can then define the completion of `μ` as the
measure on the least `σ`-algebra that also contains all null sets, by defining the measure to be `0`
on the null sets.
## Main statements
* `completion` is the completion of a measure to all null measurable sets.
* `Measure.ofMeasurable` and `OuterMeasure.toMeasure` are two important ways to define a measure.
## Implementation notes
Given `μ : Measure α`, `μ s` is the value of the *outer measure* applied to `s`.
This conveniently allows us to apply the measure to sets without proving that they are measurable.
We get countable subadditivity for all sets, but only countable additivity for measurable sets.
You often don't want to define a measure via its constructor.
Two ways that are sometimes more convenient:
* `Measure.ofMeasurable` is a way to define a measure by only giving its value on measurable sets
and proving the properties (1) and (2) mentioned above.
* `OuterMeasure.toMeasure` is a way of obtaining a measure from an outer measure by showing that
all measurable sets in the measurable space are Carathéodory measurable.
To prove that two measures are equal, there are multiple options:
* `ext`: two measures are equal if they are equal on all measurable sets.
* `ext_of_generateFrom_of_iUnion`: two measures are equal if they are equal on a π-system generating
the measurable sets, if the π-system contains a spanning increasing sequence of sets where the
measures take finite value (in particular the measures are σ-finite). This is a special case of
the more general `ext_of_generateFrom_of_cover`
* `ext_of_generate_finite`: two finite measures are equal if they are equal on a π-system
generating the measurable sets. This is a special case of `ext_of_generateFrom_of_iUnion` using
`C ∪ {univ}`, but is easier to work with.
A `MeasureSpace` is a class that is a measurable space with a canonical measure.
The measure is denoted `volume`.
## References
* <https://en.wikipedia.org/wiki/Measure_(mathematics)>
* <https://en.wikipedia.org/wiki/Complete_measure>
* <https://en.wikipedia.org/wiki/Almost_everywhere>
## Tags
measure, almost everywhere, measure space, completion, null set, null measurable set
-/
noncomputable section
open Set
open Filter hiding map
open Function MeasurableSpace Topology Filter ENNReal NNReal Interval MeasureTheory
open scoped symmDiff
variable {α β γ δ ι R R' : Type*}
namespace MeasureTheory
section
variable {m : MeasurableSpace α} {μ μ₁ μ₂ : Measure α} {s s₁ s₂ t : Set α}
instance ae_isMeasurablyGenerated : IsMeasurablyGenerated (ae μ) :=
⟨fun _s hs =>
let ⟨t, hst, htm, htμ⟩ := exists_measurable_superset_of_null hs
⟨tᶜ, compl_mem_ae_iff.2 htμ, htm.compl, compl_subset_comm.1 hst⟩⟩
/-- See also `MeasureTheory.ae_restrict_uIoc_iff`. -/
theorem ae_uIoc_iff [LinearOrder α] {a b : α} {P : α → Prop} :
(∀ᵐ x ∂μ, x ∈ Ι a b → P x) ↔ (∀ᵐ x ∂μ, x ∈ Ioc a b → P x) ∧ ∀ᵐ x ∂μ, x ∈ Ioc b a → P x := by
simp only [uIoc_eq_union, mem_union, or_imp, eventually_and]
theorem measure_union (hd : Disjoint s₁ s₂) (h : MeasurableSet s₂) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ :=
measure_union₀ h.nullMeasurableSet hd.aedisjoint
theorem measure_union' (hd : Disjoint s₁ s₂) (h : MeasurableSet s₁) : μ (s₁ ∪ s₂) = μ s₁ + μ s₂ :=
measure_union₀' h.nullMeasurableSet hd.aedisjoint
theorem measure_inter_add_diff (s : Set α) (ht : MeasurableSet t) : μ (s ∩ t) + μ (s \ t) = μ s :=
measure_inter_add_diff₀ _ ht.nullMeasurableSet
theorem measure_diff_add_inter (s : Set α) (ht : MeasurableSet t) : μ (s \ t) + μ (s ∩ t) = μ s :=
(add_comm _ _).trans (measure_inter_add_diff s ht)
theorem measure_diff_eq_top (hs : μ s = ∞) (ht : μ t ≠ ∞) : μ (s \ t) = ∞ := by
contrapose! hs
exact ((measure_mono (subset_diff_union s t)).trans_lt
((measure_union_le _ _).trans_lt (ENNReal.add_lt_top.2 ⟨hs.lt_top, ht.lt_top⟩))).ne
theorem measure_union_add_inter (s : Set α) (ht : MeasurableSet t) :
μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by
rw [← measure_inter_add_diff (s ∪ t) ht, Set.union_inter_cancel_right, union_diff_right, ←
measure_inter_add_diff s ht]
ac_rfl
theorem measure_union_add_inter' (hs : MeasurableSet s) (t : Set α) :
μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by
rw [union_comm, inter_comm, measure_union_add_inter t hs, add_comm]
lemma measure_symmDiff_eq (hs : NullMeasurableSet s μ) (ht : NullMeasurableSet t μ) :
μ (s ∆ t) = μ (s \ t) + μ (t \ s) := by
simpa only [symmDiff_def, sup_eq_union]
using measure_union₀ (ht.diff hs) disjoint_sdiff_sdiff.aedisjoint
lemma measure_symmDiff_le (s t u : Set α) :
μ (s ∆ u) ≤ μ (s ∆ t) + μ (t ∆ u) :=
le_trans (μ.mono <| symmDiff_triangle s t u) (measure_union_le (s ∆ t) (t ∆ u))
theorem measure_symmDiff_eq_top (hs : μ s ≠ ∞) (ht : μ t = ∞) : μ (s ∆ t) = ∞ :=
measure_mono_top subset_union_right (measure_diff_eq_top ht hs)
theorem measure_add_measure_compl (h : MeasurableSet s) : μ s + μ sᶜ = μ univ :=
measure_add_measure_compl₀ h.nullMeasurableSet
theorem measure_biUnion₀ {s : Set β} {f : β → Set α} (hs : s.Countable)
(hd : s.Pairwise (AEDisjoint μ on f)) (h : ∀ b ∈ s, NullMeasurableSet (f b) μ) :
μ (⋃ b ∈ s, f b) = ∑' p : s, μ (f p) := by
haveI := hs.toEncodable
rw [biUnion_eq_iUnion]
exact measure_iUnion₀ (hd.on_injective Subtype.coe_injective fun x => x.2) fun x => h x x.2
theorem measure_biUnion {s : Set β} {f : β → Set α} (hs : s.Countable) (hd : s.PairwiseDisjoint f)
(h : ∀ b ∈ s, MeasurableSet (f b)) : μ (⋃ b ∈ s, f b) = ∑' p : s, μ (f p) :=
measure_biUnion₀ hs hd.aedisjoint fun b hb => (h b hb).nullMeasurableSet
theorem measure_sUnion₀ {S : Set (Set α)} (hs : S.Countable) (hd : S.Pairwise (AEDisjoint μ))
(h : ∀ s ∈ S, NullMeasurableSet s μ) : μ (⋃₀ S) = ∑' s : S, μ s := by
rw [sUnion_eq_biUnion, measure_biUnion₀ hs hd h]
theorem measure_sUnion {S : Set (Set α)} (hs : S.Countable) (hd : S.Pairwise Disjoint)
(h : ∀ s ∈ S, MeasurableSet s) : μ (⋃₀ S) = ∑' s : S, μ s := by
rw [sUnion_eq_biUnion, measure_biUnion hs hd h]
theorem measure_biUnion_finset₀ {s : Finset ι} {f : ι → Set α}
(hd : Set.Pairwise (↑s) (AEDisjoint μ on f)) (hm : ∀ b ∈ s, NullMeasurableSet (f b) μ) :
μ (⋃ b ∈ s, f b) = ∑ p ∈ s, μ (f p) := by
rw [← Finset.sum_attach, Finset.attach_eq_univ, ← tsum_fintype]
exact measure_biUnion₀ s.countable_toSet hd hm
theorem measure_biUnion_finset {s : Finset ι} {f : ι → Set α} (hd : PairwiseDisjoint (↑s) f)
(hm : ∀ b ∈ s, MeasurableSet (f b)) : μ (⋃ b ∈ s, f b) = ∑ p ∈ s, μ (f p) :=
measure_biUnion_finset₀ hd.aedisjoint fun b hb => (hm b hb).nullMeasurableSet
/-- The measure of an a.e. disjoint union (even uncountable) of null-measurable sets is at least
the sum of the measures of the sets. -/
theorem tsum_meas_le_meas_iUnion_of_disjoint₀ {ι : Type*} {_ : MeasurableSpace α} (μ : Measure α)
{As : ι → Set α} (As_mble : ∀ i : ι, NullMeasurableSet (As i) μ)
(As_disj : Pairwise (AEDisjoint μ on As)) : (∑' i, μ (As i)) ≤ μ (⋃ i, As i) := by
rw [ENNReal.tsum_eq_iSup_sum, iSup_le_iff]
intro s
simp only [← measure_biUnion_finset₀ (fun _i _hi _j _hj hij => As_disj hij) fun i _ => As_mble i]
gcongr
exact iUnion_subset fun _ ↦ Subset.rfl
/-- The measure of a disjoint union (even uncountable) of measurable sets is at least the sum of
the measures of the sets. -/
theorem tsum_meas_le_meas_iUnion_of_disjoint {ι : Type*} {_ : MeasurableSpace α} (μ : Measure α)
{As : ι → Set α} (As_mble : ∀ i : ι, MeasurableSet (As i))
(As_disj : Pairwise (Disjoint on As)) : (∑' i, μ (As i)) ≤ μ (⋃ i, As i) :=
tsum_meas_le_meas_iUnion_of_disjoint₀ μ (fun i ↦ (As_mble i).nullMeasurableSet)
(fun _ _ h ↦ Disjoint.aedisjoint (As_disj h))
/-- If `s` is a countable set, then the measure of its preimage can be found as the sum of measures
of the fibers `f ⁻¹' {y}`. -/
theorem tsum_measure_preimage_singleton {s : Set β} (hs : s.Countable) {f : α → β}
(hf : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y})) : (∑' b : s, μ (f ⁻¹' {↑b})) = μ (f ⁻¹' s) := by
rw [← Set.biUnion_preimage_singleton, measure_biUnion hs (pairwiseDisjoint_fiber f s) hf]
lemma measure_preimage_eq_zero_iff_of_countable {s : Set β} {f : α → β} (hs : s.Countable) :
μ (f ⁻¹' s) = 0 ↔ ∀ x ∈ s, μ (f ⁻¹' {x}) = 0 := by
rw [← biUnion_preimage_singleton, measure_biUnion_null_iff hs]
/-- If `s` is a `Finset`, then the measure of its preimage can be found as the sum of measures
of the fibers `f ⁻¹' {y}`. -/
| Mathlib/MeasureTheory/Measure/MeasureSpace.lean | 209 | 211 | theorem sum_measure_preimage_singleton (s : Finset β) {f : α → β}
(hf : ∀ y ∈ s, MeasurableSet (f ⁻¹' {y})) : (∑ b ∈ s, μ (f ⁻¹' {b})) = μ (f ⁻¹' ↑s) := by | simp only [← measure_biUnion_finset (pairwiseDisjoint_fiber f s) hf, |
/-
Copyright (c) 2022 David Loeffler. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Loeffler, Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Analysis.Convex.SpecificFunctions.Deriv
import Mathlib.Analysis.SpecialFunctions.Trigonometric.ArctanDeriv
/-!
# Polynomial bounds for trigonometric functions
## Main statements
This file contains upper and lower bounds for real trigonometric functions in terms
of polynomials. See `Trigonometric.Basic` for more elementary inequalities, establishing
the ranges of these functions, and their monotonicity in suitable intervals.
Here we prove the following:
* `sin_lt`: for `x > 0` we have `sin x < x`.
* `sin_gt_sub_cube`: For `0 < x ≤ 1` we have `x - x ^ 3 / 4 < sin x`.
* `lt_tan`: for `0 < x < π/2` we have `x < tan x`.
* `cos_le_one_div_sqrt_sq_add_one` and `cos_lt_one_div_sqrt_sq_add_one`: for
`-3 * π / 2 ≤ x ≤ 3 * π / 2`, we have `cos x ≤ 1 / sqrt (x ^ 2 + 1)`, with strict inequality if
`x ≠ 0`. (This bound is not quite optimal, but not far off)
## Tags
sin, cos, tan, angle
-/
open Set
namespace Real
variable {x : ℝ}
/-- For 0 < x, we have sin x < x. -/
theorem sin_lt (h : 0 < x) : sin x < x := by
rcases lt_or_le 1 x with h' | h'
· exact (sin_le_one x).trans_lt h'
have hx : |x| = x := abs_of_nonneg h.le
have := le_of_abs_le (sin_bound <| show |x| ≤ 1 by rwa [hx])
rw [sub_le_iff_le_add', hx] at this
apply this.trans_lt
rw [sub_add, sub_lt_self_iff, sub_pos, div_eq_mul_inv (x ^ 3)]
refine mul_lt_mul' ?_ (by norm_num) (by norm_num) (pow_pos h 3)
apply pow_le_pow_of_le_one h.le h'
norm_num
lemma sin_le (hx : 0 ≤ x) : sin x ≤ x := by
obtain rfl | hx := hx.eq_or_lt
· simp
· exact (sin_lt hx).le
lemma lt_sin (hx : x < 0) : x < sin x := by simpa using sin_lt <| neg_pos.2 hx
lemma le_sin (hx : x ≤ 0) : x ≤ sin x := by simpa using sin_le <| neg_nonneg.2 hx
| Mathlib/Analysis/SpecialFunctions/Trigonometric/Bounds.lean | 58 | 58 | theorem lt_sin_mul {x : ℝ} (hx : 0 < x) (hx' : x < 1) : x < sin (π / 2 * x) := by | |
/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Patrick Massot
-/
import Mathlib.Topology.Neighborhoods
/-!
# Neighborhoods of a set
In this file we define the filter `𝓝ˢ s` or `nhdsSet s` consisting of all neighborhoods of a set
`s`.
## Main Properties
There are a couple different notions equivalent to `s ∈ 𝓝ˢ t`:
* `s ⊆ interior t` using `subset_interior_iff_mem_nhdsSet`
* `∀ x : X, x ∈ t → s ∈ 𝓝 x` using `mem_nhdsSet_iff_forall`
* `∃ U : Set X, IsOpen U ∧ t ⊆ U ∧ U ⊆ s` using `mem_nhdsSet_iff_exists`
Furthermore, we have the following results:
* `monotone_nhdsSet`: `𝓝ˢ` is monotone
* In T₁-spaces, `𝓝ˢ`is strictly monotone and hence injective:
`strict_mono_nhdsSet`/`injective_nhdsSet`. These results are in `Mathlib.Topology.Separation`.
-/
open Set Filter Topology
variable {X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y] {f : Filter X}
{s t s₁ s₂ t₁ t₂ : Set X} {x : X}
theorem nhdsSet_diagonal (X) [TopologicalSpace (X × X)] :
𝓝ˢ (diagonal X) = ⨆ (x : X), 𝓝 (x, x) := by
rw [nhdsSet, ← range_diag, ← range_comp]
rfl
theorem mem_nhdsSet_iff_forall : s ∈ 𝓝ˢ t ↔ ∀ x : X, x ∈ t → s ∈ 𝓝 x := by
simp_rw [nhdsSet, Filter.mem_sSup, forall_mem_image]
lemma nhdsSet_le : 𝓝ˢ s ≤ f ↔ ∀ x ∈ s, 𝓝 x ≤ f := by simp [nhdsSet]
theorem bUnion_mem_nhdsSet {t : X → Set X} (h : ∀ x ∈ s, t x ∈ 𝓝 x) : (⋃ x ∈ s, t x) ∈ 𝓝ˢ s :=
mem_nhdsSet_iff_forall.2 fun x hx => mem_of_superset (h x hx) <|
subset_iUnion₂ (s := fun x _ => t x) x hx
theorem subset_interior_iff_mem_nhdsSet : s ⊆ interior t ↔ t ∈ 𝓝ˢ s := by
simp_rw [mem_nhdsSet_iff_forall, subset_interior_iff_nhds]
theorem disjoint_principal_nhdsSet : Disjoint (𝓟 s) (𝓝ˢ t) ↔ Disjoint (closure s) t := by
rw [disjoint_principal_left, ← subset_interior_iff_mem_nhdsSet, interior_compl,
subset_compl_iff_disjoint_left]
theorem disjoint_nhdsSet_principal : Disjoint (𝓝ˢ s) (𝓟 t) ↔ Disjoint s (closure t) := by
rw [disjoint_comm, disjoint_principal_nhdsSet, disjoint_comm]
theorem mem_nhdsSet_iff_exists : s ∈ 𝓝ˢ t ↔ ∃ U : Set X, IsOpen U ∧ t ⊆ U ∧ U ⊆ s := by
rw [← subset_interior_iff_mem_nhdsSet, subset_interior_iff]
/-- A proposition is true on a set neighborhood of `s` iff it is true on a larger open set -/
theorem eventually_nhdsSet_iff_exists {p : X → Prop} :
(∀ᶠ x in 𝓝ˢ s, p x) ↔ ∃ t, IsOpen t ∧ s ⊆ t ∧ ∀ x, x ∈ t → p x :=
mem_nhdsSet_iff_exists
/-- A proposition is true on a set neighborhood of `s`
iff it is eventually true near each point in the set. -/
theorem eventually_nhdsSet_iff_forall {p : X → Prop} :
(∀ᶠ x in 𝓝ˢ s, p x) ↔ ∀ x, x ∈ s → ∀ᶠ y in 𝓝 x, p y :=
mem_nhdsSet_iff_forall
theorem hasBasis_nhdsSet (s : Set X) : (𝓝ˢ s).HasBasis (fun U => IsOpen U ∧ s ⊆ U) fun U => U :=
⟨fun t => by simp [mem_nhdsSet_iff_exists, and_assoc]⟩
@[simp]
lemma lift'_nhdsSet_interior (s : Set X) : (𝓝ˢ s).lift' interior = 𝓝ˢ s :=
(hasBasis_nhdsSet s).lift'_interior_eq_self fun _ ↦ And.left
lemma Filter.HasBasis.nhdsSet_interior {ι : Sort*} {p : ι → Prop} {s : ι → Set X} {t : Set X}
(h : (𝓝ˢ t).HasBasis p s) : (𝓝ˢ t).HasBasis p (interior <| s ·) :=
lift'_nhdsSet_interior t ▸ h.lift'_interior
theorem IsOpen.mem_nhdsSet (hU : IsOpen s) : s ∈ 𝓝ˢ t ↔ t ⊆ s := by
rw [← subset_interior_iff_mem_nhdsSet, hU.interior_eq]
/-- An open set belongs to its own set neighborhoods filter. -/
theorem IsOpen.mem_nhdsSet_self (ho : IsOpen s) : s ∈ 𝓝ˢ s := ho.mem_nhdsSet.mpr Subset.rfl
theorem principal_le_nhdsSet : 𝓟 s ≤ 𝓝ˢ s := fun _s hs =>
(subset_interior_iff_mem_nhdsSet.mpr hs).trans interior_subset
theorem subset_of_mem_nhdsSet (h : t ∈ 𝓝ˢ s) : s ⊆ t := principal_le_nhdsSet h
theorem Filter.Eventually.self_of_nhdsSet {p : X → Prop} (h : ∀ᶠ x in 𝓝ˢ s, p x) : ∀ x ∈ s, p x :=
principal_le_nhdsSet h
nonrec theorem Filter.EventuallyEq.self_of_nhdsSet {Y} {f g : X → Y} (h : f =ᶠ[𝓝ˢ s] g) :
EqOn f g s :=
h.self_of_nhdsSet
@[simp]
theorem nhdsSet_eq_principal_iff : 𝓝ˢ s = 𝓟 s ↔ IsOpen s := by
rw [← principal_le_nhdsSet.le_iff_eq, le_principal_iff, mem_nhdsSet_iff_forall,
isOpen_iff_mem_nhds]
alias ⟨_, IsOpen.nhdsSet_eq⟩ := nhdsSet_eq_principal_iff
@[simp]
theorem nhdsSet_interior : 𝓝ˢ (interior s) = 𝓟 (interior s) :=
isOpen_interior.nhdsSet_eq
@[simp]
theorem nhdsSet_singleton : 𝓝ˢ {x} = 𝓝 x := by simp [nhdsSet]
theorem mem_nhdsSet_interior : s ∈ 𝓝ˢ (interior s) :=
subset_interior_iff_mem_nhdsSet.mp Subset.rfl
@[simp]
theorem nhdsSet_empty : 𝓝ˢ (∅ : Set X) = ⊥ := by rw [isOpen_empty.nhdsSet_eq, principal_empty]
theorem mem_nhdsSet_empty : s ∈ 𝓝ˢ (∅ : Set X) := by simp
@[simp]
theorem nhdsSet_univ : 𝓝ˢ (univ : Set X) = ⊤ := by rw [isOpen_univ.nhdsSet_eq, principal_univ]
@[gcongr, mono]
theorem nhdsSet_mono (h : s ⊆ t) : 𝓝ˢ s ≤ 𝓝ˢ t :=
sSup_le_sSup <| image_subset _ h
theorem monotone_nhdsSet : Monotone (𝓝ˢ : Set X → Filter X) := fun _ _ => nhdsSet_mono
theorem nhds_le_nhdsSet (h : x ∈ s) : 𝓝 x ≤ 𝓝ˢ s :=
le_sSup <| mem_image_of_mem _ h
@[simp]
| Mathlib/Topology/NhdsSet.lean | 135 | 135 | theorem nhdsSet_union (s t : Set X) : 𝓝ˢ (s ∪ t) = 𝓝ˢ s ⊔ 𝓝ˢ t := by | |
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Algebra.Order.Group.Finset
import Mathlib.Data.Finsupp.Order
import Mathlib.Data.Sym.Basic
/-!
# Equivalence between `Multiset` and `ℕ`-valued finitely supported functions
This defines `Finsupp.toMultiset` the equivalence between `α →₀ ℕ` and `Multiset α`, along
with `Multiset.toFinsupp` the reverse equivalence and `Finsupp.orderIsoMultiset` (the equivalence
promoted to an order isomorphism).
-/
open Finset
variable {α β ι : Type*}
namespace Finsupp
/-- Given `f : α →₀ ℕ`, `f.toMultiset` is the multiset with multiplicities given by the values of
`f` on the elements of `α`. We define this function as an `AddMonoidHom`.
Under the additional assumption of `[DecidableEq α]`, this is available as
`Multiset.toFinsupp : Multiset α ≃+ (α →₀ ℕ)`; the two declarations are separate as this assumption
is only needed for one direction. -/
def toMultiset : (α →₀ ℕ) →+ Multiset α where
toFun f := Finsupp.sum f fun a n => n • {a}
-- Porting note: have to specify `h` or add a `dsimp only` before `sum_add_index'`.
-- see also: https://github.com/leanprover-community/mathlib4/issues/12129
map_add' _f _g := sum_add_index' (h := fun _ n => n • _)
(fun _ ↦ zero_nsmul _) (fun _ ↦ add_nsmul _)
map_zero' := sum_zero_index
theorem toMultiset_zero : toMultiset (0 : α →₀ ℕ) = 0 :=
rfl
theorem toMultiset_add (m n : α →₀ ℕ) : toMultiset (m + n) = toMultiset m + toMultiset n :=
toMultiset.map_add m n
theorem toMultiset_apply (f : α →₀ ℕ) : toMultiset f = f.sum fun a n => n • {a} :=
rfl
@[simp]
theorem toMultiset_single (a : α) (n : ℕ) : toMultiset (single a n) = n • {a} := by
rw [toMultiset_apply, sum_single_index]; apply zero_nsmul
theorem toMultiset_sum {f : ι → α →₀ ℕ} (s : Finset ι) :
Finsupp.toMultiset (∑ i ∈ s, f i) = ∑ i ∈ s, Finsupp.toMultiset (f i) :=
map_sum Finsupp.toMultiset _ _
theorem toMultiset_sum_single (s : Finset ι) (n : ℕ) :
Finsupp.toMultiset (∑ i ∈ s, single i n) = n • s.val := by
simp_rw [toMultiset_sum, Finsupp.toMultiset_single, Finset.sum_nsmul, sum_multiset_singleton]
@[simp]
| Mathlib/Data/Finsupp/Multiset.lean | 61 | 63 | theorem card_toMultiset (f : α →₀ ℕ) : Multiset.card (toMultiset f) = f.sum fun _ => id := by | simp [toMultiset_apply, map_finsuppSum, Function.id_def] |
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Patrick Massot, Casper Putz, Anne Baanen
-/
import Mathlib.Data.Matrix.Basis
import Mathlib.Data.Matrix.Block
import Mathlib.Data.Matrix.RowCol
import Mathlib.Data.Matrix.Notation
/-!
# Trace of a matrix
This file defines the trace of a matrix, the map sending a matrix to the sum of its diagonal
entries.
See also `LinearAlgebra.Trace` for the trace of an endomorphism.
## Tags
matrix, trace, diagonal
-/
open Matrix
namespace Matrix
variable {ι m n p : Type*} {α R S : Type*}
variable [Fintype m] [Fintype n] [Fintype p]
section AddCommMonoid
variable [AddCommMonoid R]
/-- The trace of a square matrix. For more bundled versions, see:
* `Matrix.traceAddMonoidHom`
* `Matrix.traceLinearMap`
-/
def trace (A : Matrix n n R) : R :=
∑ i, diag A i
lemma trace_diagonal {o} [Fintype o] [DecidableEq o] (d : o → R) :
trace (diagonal d) = ∑ i, d i := by
simp only [trace, diag_apply, diagonal_apply_eq]
variable (n R)
@[simp]
theorem trace_zero : trace (0 : Matrix n n R) = 0 :=
(Finset.sum_const (0 : R)).trans <| smul_zero _
variable {n R}
@[simp]
lemma trace_eq_zero_of_isEmpty [IsEmpty n] (A : Matrix n n R) : trace A = 0 := by simp [trace]
@[simp]
theorem trace_add (A B : Matrix n n R) : trace (A + B) = trace A + trace B :=
Finset.sum_add_distrib
@[simp]
theorem trace_smul [DistribSMul α R] (r : α) (A : Matrix n n R) :
trace (r • A) = r • trace A :=
Finset.smul_sum.symm
@[simp]
theorem trace_transpose (A : Matrix n n R) : trace Aᵀ = trace A :=
rfl
@[simp]
theorem trace_conjTranspose [StarAddMonoid R] (A : Matrix n n R) : trace Aᴴ = star (trace A) :=
(star_sum _ _).symm
variable (n α R)
/-- `Matrix.trace` as an `AddMonoidHom` -/
@[simps]
def traceAddMonoidHom : Matrix n n R →+ R where
toFun := trace
map_zero' := trace_zero n R
map_add' := trace_add
/-- `Matrix.trace` as a `LinearMap` -/
@[simps]
def traceLinearMap [Semiring α] [Module α R] : Matrix n n R →ₗ[α] R where
toFun := trace
map_add' := trace_add
map_smul' := trace_smul
variable {n α R}
@[simp]
theorem trace_list_sum (l : List (Matrix n n R)) : trace l.sum = (l.map trace).sum :=
map_list_sum (traceAddMonoidHom n R) l
@[simp]
theorem trace_multiset_sum (s : Multiset (Matrix n n R)) : trace s.sum = (s.map trace).sum :=
map_multiset_sum (traceAddMonoidHom n R) s
@[simp]
theorem trace_sum (s : Finset ι) (f : ι → Matrix n n R) :
trace (∑ i ∈ s, f i) = ∑ i ∈ s, trace (f i) :=
map_sum (traceAddMonoidHom n R) f s
theorem _root_.AddMonoidHom.map_trace [AddCommMonoid S] {F : Type*} [FunLike F R S]
[AddMonoidHomClass F R S] (f : F) (A : Matrix n n R) :
f (trace A) = trace ((f : R →+ S).mapMatrix A) :=
map_sum f (fun i => diag A i) Finset.univ
lemma trace_blockDiagonal [DecidableEq p] (M : p → Matrix n n R) :
trace (blockDiagonal M) = ∑ i, trace (M i) := by
simp [blockDiagonal, trace, Finset.sum_comm (γ := n), Fintype.sum_prod_type]
lemma trace_blockDiagonal' [DecidableEq p] {m : p → Type*} [∀ i, Fintype (m i)]
(M : ∀ i, Matrix (m i) (m i) R) :
trace (blockDiagonal' M) = ∑ i, trace (M i) := by
simp [blockDiagonal', trace, Finset.sum_sigma']
end AddCommMonoid
section AddCommGroup
variable [AddCommGroup R]
@[simp]
theorem trace_sub (A B : Matrix n n R) : trace (A - B) = trace A - trace B :=
Finset.sum_sub_distrib
@[simp]
theorem trace_neg (A : Matrix n n R) : trace (-A) = -trace A :=
Finset.sum_neg_distrib
end AddCommGroup
section One
variable [DecidableEq n] [AddCommMonoidWithOne R]
@[simp]
theorem trace_one : trace (1 : Matrix n n R) = Fintype.card n := by
simp_rw [trace, diag_one, Pi.one_def, Finset.sum_const, nsmul_one, Finset.card_univ]
end One
section Mul
@[simp]
theorem trace_transpose_mul [AddCommMonoid R] [Mul R] (A : Matrix m n R) (B : Matrix n m R) :
trace (Aᵀ * Bᵀ) = trace (A * B) :=
Finset.sum_comm
| Mathlib/LinearAlgebra/Matrix/Trace.lean | 154 | 155 | theorem trace_mul_comm [AddCommMonoid R] [CommMagma R] (A : Matrix m n R) (B : Matrix n m R) :
trace (A * B) = trace (B * A) := by | rw [← trace_transpose, ← trace_transpose_mul, transpose_mul] |
/-
Copyright (c) 2020 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.Algebra.IsPrimePow
import Mathlib.Algebra.Order.BigOperators.Group.Finset
import Mathlib.Algebra.Order.Ring.Int
import Mathlib.Algebra.Ring.CharZero
import Mathlib.Data.Nat.Cast.Order.Ring
import Mathlib.Data.Nat.PrimeFin
import Mathlib.Order.Interval.Finset.Nat
/-!
# Divisor Finsets
This file defines sets of divisors of a natural number. This is particularly useful as background
for defining Dirichlet convolution.
## Main Definitions
Let `n : ℕ`. All of the following definitions are in the `Nat` namespace:
* `divisors n` is the `Finset` of natural numbers that divide `n`.
* `properDivisors n` is the `Finset` of natural numbers that divide `n`, other than `n`.
* `divisorsAntidiagonal n` is the `Finset` of pairs `(x,y)` such that `x * y = n`.
* `Perfect n` is true when `n` is positive and the sum of `properDivisors n` is `n`.
## Conventions
Since `0` has infinitely many divisors, none of the definitions in this file make sense for it.
Therefore we adopt the convention that `Nat.divisors 0`, `Nat.properDivisors 0`,
`Nat.divisorsAntidiagonal 0` and `Int.divisorsAntidiag 0` are all `∅`.
## Tags
divisors, perfect numbers
-/
open Finset
namespace Nat
variable (n : ℕ)
/-- `divisors n` is the `Finset` of divisors of `n`. By convention, we set `divisors 0 = ∅`. -/
def divisors : Finset ℕ := {d ∈ Ico 1 (n + 1) | d ∣ n}
/-- `properDivisors n` is the `Finset` of divisors of `n`, other than `n`.
By convention, we set `properDivisors 0 = ∅`. -/
def properDivisors : Finset ℕ := {d ∈ Ico 1 n | d ∣ n}
/-- Pairs of divisors of a natural number as a finset.
`n.divisorsAntidiagonal` is the finset of pairs `(a, b) : ℕ × ℕ` such that `a * b = n`.
By convention, we set `Nat.divisorsAntidiagonal 0 = ∅`.
O(n). -/
def divisorsAntidiagonal : Finset (ℕ × ℕ) :=
(Icc 1 n).filterMap (fun x ↦ let y := n / x; if x * y = n then some (x, y) else none)
fun x₁ x₂ (x, y) hx₁ hx₂ ↦ by aesop
/-- Pairs of divisors of a natural number, as a list.
`n.divisorsAntidiagonalList` is the list of pairs `(a, b) : ℕ × ℕ` such that `a * b = n`, ordered
by increasing `a`. By convention, we set `Nat.divisorsAntidiagonalList 0 = []`.
-/
def divisorsAntidiagonalList (n : ℕ) : List (ℕ × ℕ) :=
(List.range' 1 n).filterMap
(fun x ↦ let y := n / x; if x * y = n then some (x, y) else none)
variable {n}
@[simp]
theorem filter_dvd_eq_divisors (h : n ≠ 0) : {d ∈ range n.succ | d ∣ n} = n.divisors := by
ext
simp only [divisors, mem_filter, mem_range, mem_Ico, and_congr_left_iff, iff_and_self]
exact fun ha _ => succ_le_iff.mpr (pos_of_dvd_of_pos ha h.bot_lt)
@[simp]
theorem filter_dvd_eq_properDivisors (h : n ≠ 0) : {d ∈ range n | d ∣ n} = n.properDivisors := by
ext
simp only [properDivisors, mem_filter, mem_range, mem_Ico, and_congr_left_iff, iff_and_self]
exact fun ha _ => succ_le_iff.mpr (pos_of_dvd_of_pos ha h.bot_lt)
theorem properDivisors.not_self_mem : ¬n ∈ properDivisors n := by simp [properDivisors]
@[simp]
theorem mem_properDivisors {m : ℕ} : n ∈ properDivisors m ↔ n ∣ m ∧ n < m := by
rcases eq_or_ne m 0 with (rfl | hm); · simp [properDivisors]
simp only [and_comm, ← filter_dvd_eq_properDivisors hm, mem_filter, mem_range]
theorem insert_self_properDivisors (h : n ≠ 0) : insert n (properDivisors n) = divisors n := by
rw [divisors, properDivisors, Ico_succ_right_eq_insert_Ico (one_le_iff_ne_zero.2 h),
Finset.filter_insert, if_pos (dvd_refl n)]
theorem cons_self_properDivisors (h : n ≠ 0) :
cons n (properDivisors n) properDivisors.not_self_mem = divisors n := by
rw [cons_eq_insert, insert_self_properDivisors h]
@[simp]
theorem mem_divisors {m : ℕ} : n ∈ divisors m ↔ n ∣ m ∧ m ≠ 0 := by
rcases eq_or_ne m 0 with (rfl | hm); · simp [divisors]
simp only [hm, Ne, not_false_iff, and_true, ← filter_dvd_eq_divisors hm, mem_filter,
mem_range, and_iff_right_iff_imp, Nat.lt_succ_iff]
exact le_of_dvd hm.bot_lt
theorem one_mem_divisors : 1 ∈ divisors n ↔ n ≠ 0 := by simp
theorem mem_divisors_self (n : ℕ) (h : n ≠ 0) : n ∈ n.divisors :=
mem_divisors.2 ⟨dvd_rfl, h⟩
theorem dvd_of_mem_divisors {m : ℕ} (h : n ∈ divisors m) : n ∣ m := by
cases m
· apply dvd_zero
· simp [mem_divisors.1 h]
@[simp]
theorem mem_divisorsAntidiagonal {x : ℕ × ℕ} :
x ∈ divisorsAntidiagonal n ↔ x.fst * x.snd = n ∧ n ≠ 0 := by
obtain ⟨a, b⟩ := x
simp only [divisorsAntidiagonal, mul_div_eq_iff_dvd, mem_filterMap, mem_Icc, one_le_iff_ne_zero,
Option.ite_none_right_eq_some, Option.some.injEq, Prod.ext_iff, and_left_comm, exists_eq_left]
constructor
· rintro ⟨han, ⟨ha, han'⟩, rfl⟩
simp [Nat.mul_div_eq_iff_dvd, han]
omega
· rintro ⟨rfl, hab⟩
rw [mul_ne_zero_iff] at hab
simpa [hab.1, hab.2] using Nat.le_mul_of_pos_right _ hab.2.bot_lt
@[simp] lemma divisorsAntidiagonalList_zero : divisorsAntidiagonalList 0 = [] := rfl
@[simp] lemma divisorsAntidiagonalList_one : divisorsAntidiagonalList 1 = [(1, 1)] := rfl
@[simp]
lemma toFinset_divisorsAntidiagonalList {n : ℕ} :
n.divisorsAntidiagonalList.toFinset = n.divisorsAntidiagonal := by
rw [divisorsAntidiagonalList, divisorsAntidiagonal, List.toFinset_filterMap (f_inj := by aesop),
List.toFinset_range'_1_1]
lemma sorted_divisorsAntidiagonalList_fst {n : ℕ} :
n.divisorsAntidiagonalList.Sorted (·.fst < ·.fst) := by
refine (List.sorted_lt_range' _ _ Nat.one_ne_zero).filterMap fun a b c d h h' ha => ?_
rw [Option.ite_none_right_eq_some, Option.some.injEq] at h h'
simpa [← h.right, ← h'.right]
lemma sorted_divisorsAntidiagonalList_snd {n : ℕ} :
n.divisorsAntidiagonalList.Sorted (·.snd > ·.snd) := by
obtain rfl | hn := eq_or_ne n 0
· simp
refine (List.sorted_lt_range' _ _ Nat.one_ne_zero).filterMap ?_
simp only [Option.ite_none_right_eq_some, Option.some.injEq, gt_iff_lt, and_imp, Prod.forall,
Prod.mk.injEq]
rintro a b _ _ _ _ ha rfl rfl hb rfl rfl hab
rwa [Nat.div_lt_div_left hn ⟨_, hb.symm⟩ ⟨_, ha.symm⟩]
lemma nodup_divisorsAntidiagonalList {n : ℕ} : n.divisorsAntidiagonalList.Nodup :=
have : IsIrrefl (ℕ × ℕ) (·.fst < ·.fst) := ⟨by simp⟩
sorted_divisorsAntidiagonalList_fst.nodup
/-- The `Finset` and `List` versions agree by definition. -/
@[simp]
theorem val_divisorsAntidiagonal (n : ℕ) :
(divisorsAntidiagonal n).val = divisorsAntidiagonalList n :=
rfl
@[simp]
lemma mem_divisorsAntidiagonalList {n : ℕ} {a : ℕ × ℕ} :
a ∈ n.divisorsAntidiagonalList ↔ a.1 * a.2 = n ∧ n ≠ 0 := by
rw [← List.mem_toFinset, toFinset_divisorsAntidiagonalList, mem_divisorsAntidiagonal]
@[simp high]
lemma swap_mem_divisorsAntidiagonalList {a : ℕ × ℕ} :
a.swap ∈ n.divisorsAntidiagonalList ↔ a ∈ n.divisorsAntidiagonalList := by simp [mul_comm]
lemma reverse_divisorsAntidiagonalList (n : ℕ) :
n.divisorsAntidiagonalList.reverse = n.divisorsAntidiagonalList.map .swap := by
have : IsAsymm (ℕ × ℕ) (·.snd < ·.snd) := ⟨fun _ _ ↦ lt_asymm⟩
refine List.eq_of_perm_of_sorted ?_ sorted_divisorsAntidiagonalList_snd.reverse <|
sorted_divisorsAntidiagonalList_fst.map _ fun _ _ ↦ id
simp [List.reverse_perm', List.perm_ext_iff_of_nodup nodup_divisorsAntidiagonalList
(nodup_divisorsAntidiagonalList.map Prod.swap_injective), mul_comm]
lemma ne_zero_of_mem_divisorsAntidiagonal {p : ℕ × ℕ} (hp : p ∈ n.divisorsAntidiagonal) :
p.1 ≠ 0 ∧ p.2 ≠ 0 := by
obtain ⟨hp₁, hp₂⟩ := Nat.mem_divisorsAntidiagonal.mp hp
exact mul_ne_zero_iff.mp (hp₁.symm ▸ hp₂)
lemma left_ne_zero_of_mem_divisorsAntidiagonal {p : ℕ × ℕ} (hp : p ∈ n.divisorsAntidiagonal) :
p.1 ≠ 0 :=
(ne_zero_of_mem_divisorsAntidiagonal hp).1
lemma right_ne_zero_of_mem_divisorsAntidiagonal {p : ℕ × ℕ} (hp : p ∈ n.divisorsAntidiagonal) :
p.2 ≠ 0 :=
(ne_zero_of_mem_divisorsAntidiagonal hp).2
theorem divisor_le {m : ℕ} : n ∈ divisors m → n ≤ m := by
rcases m with - | m
· simp
· simp only [mem_divisors, Nat.succ_ne_zero m, and_true, Ne, not_false_iff]
exact Nat.le_of_dvd (Nat.succ_pos m)
theorem divisors_subset_of_dvd {m : ℕ} (hzero : n ≠ 0) (h : m ∣ n) : divisors m ⊆ divisors n :=
Finset.subset_iff.2 fun _x hx => Nat.mem_divisors.mpr ⟨(Nat.mem_divisors.mp hx).1.trans h, hzero⟩
theorem card_divisors_le_self (n : ℕ) : #n.divisors ≤ n := calc
_ ≤ #(Ico 1 (n + 1)) := by
apply card_le_card
simp only [divisors, filter_subset]
_ = n := by rw [card_Ico, add_tsub_cancel_right]
theorem divisors_subset_properDivisors {m : ℕ} (hzero : n ≠ 0) (h : m ∣ n) (hdiff : m ≠ n) :
divisors m ⊆ properDivisors n := by
apply Finset.subset_iff.2
intro x hx
exact
Nat.mem_properDivisors.2
⟨(Nat.mem_divisors.1 hx).1.trans h,
lt_of_le_of_lt (divisor_le hx)
(lt_of_le_of_ne (divisor_le (Nat.mem_divisors.2 ⟨h, hzero⟩)) hdiff)⟩
lemma divisors_filter_dvd_of_dvd {n m : ℕ} (hn : n ≠ 0) (hm : m ∣ n) :
{d ∈ n.divisors | d ∣ m} = m.divisors := by
ext k
simp_rw [mem_filter, mem_divisors]
exact ⟨fun ⟨_, hkm⟩ ↦ ⟨hkm, ne_zero_of_dvd_ne_zero hn hm⟩, fun ⟨hk, _⟩ ↦ ⟨⟨hk.trans hm, hn⟩, hk⟩⟩
@[simp]
theorem divisors_zero : divisors 0 = ∅ := by
ext
simp
@[simp]
theorem properDivisors_zero : properDivisors 0 = ∅ := by
ext
simp
@[simp]
lemma nonempty_divisors : (divisors n).Nonempty ↔ n ≠ 0 :=
⟨fun ⟨m, hm⟩ hn ↦ by simp [hn] at hm, fun hn ↦ ⟨1, one_mem_divisors.2 hn⟩⟩
@[simp]
lemma divisors_eq_empty : divisors n = ∅ ↔ n = 0 :=
not_nonempty_iff_eq_empty.symm.trans nonempty_divisors.not_left
theorem properDivisors_subset_divisors : properDivisors n ⊆ divisors n :=
filter_subset_filter _ <| Ico_subset_Ico_right n.le_succ
@[simp]
theorem divisors_one : divisors 1 = {1} := by
ext
simp
@[simp]
theorem properDivisors_one : properDivisors 1 = ∅ := by rw [properDivisors, Ico_self, filter_empty]
theorem pos_of_mem_divisors {m : ℕ} (h : m ∈ n.divisors) : 0 < m := by
cases m
· rw [mem_divisors, zero_dvd_iff (a := n)] at h
cases h.2 h.1
apply Nat.succ_pos
theorem pos_of_mem_properDivisors {m : ℕ} (h : m ∈ n.properDivisors) : 0 < m :=
pos_of_mem_divisors (properDivisors_subset_divisors h)
| Mathlib/NumberTheory/Divisors.lean | 264 | 266 | theorem one_mem_properDivisors_iff_one_lt : 1 ∈ n.properDivisors ↔ 1 < n := by | rw [mem_properDivisors, and_iff_right (one_dvd _)] |
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel,
Rémy Degenne, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Complex
import Qq
/-! # Power function on `ℝ`
We construct the power functions `x ^ y`, where `x` and `y` are real numbers.
-/
noncomputable section
open Real ComplexConjugate Finset Set
/-
## Definitions
-/
namespace Real
variable {x y z : ℝ}
/-- The real power function `x ^ y`, defined as the real part of the complex power function.
For `x > 0`, it is equal to `exp (y log x)`. For `x = 0`, one sets `0 ^ 0=1` and `0 ^ y=0` for
`y ≠ 0`. For `x < 0`, the definition is somewhat arbitrary as it depends on the choice of a complex
determination of the logarithm. With our conventions, it is equal to `exp (y log x) cos (π y)`. -/
noncomputable def rpow (x y : ℝ) :=
((x : ℂ) ^ (y : ℂ)).re
noncomputable instance : Pow ℝ ℝ := ⟨rpow⟩
@[simp]
theorem rpow_eq_pow (x y : ℝ) : rpow x y = x ^ y := rfl
theorem rpow_def (x y : ℝ) : x ^ y = ((x : ℂ) ^ (y : ℂ)).re := rfl
theorem rpow_def_of_nonneg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) :
x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) := by
simp only [rpow_def, Complex.cpow_def]; split_ifs <;>
simp_all [(Complex.ofReal_log hx).symm, -Complex.ofReal_mul,
(Complex.ofReal_mul _ _).symm, Complex.exp_ofReal_re, Complex.ofReal_eq_zero]
theorem rpow_def_of_pos {x : ℝ} (hx : 0 < x) (y : ℝ) : x ^ y = exp (log x * y) := by
rw [rpow_def_of_nonneg (le_of_lt hx), if_neg (ne_of_gt hx)]
theorem exp_mul (x y : ℝ) : exp (x * y) = exp x ^ y := by rw [rpow_def_of_pos (exp_pos _), log_exp]
@[simp, norm_cast]
theorem rpow_intCast (x : ℝ) (n : ℤ) : x ^ (n : ℝ) = x ^ n := by
simp only [rpow_def, ← Complex.ofReal_zpow, Complex.cpow_intCast, Complex.ofReal_intCast,
Complex.ofReal_re]
@[simp, norm_cast]
theorem rpow_natCast (x : ℝ) (n : ℕ) : x ^ (n : ℝ) = x ^ n := by simpa using rpow_intCast x n
@[simp]
theorem exp_one_rpow (x : ℝ) : exp 1 ^ x = exp x := by rw [← exp_mul, one_mul]
@[simp] lemma exp_one_pow (n : ℕ) : exp 1 ^ n = exp n := by rw [← rpow_natCast, exp_one_rpow]
theorem rpow_eq_zero_iff_of_nonneg (hx : 0 ≤ x) : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by
simp only [rpow_def_of_nonneg hx]
split_ifs <;> simp [*, exp_ne_zero]
@[simp]
lemma rpow_eq_zero (hx : 0 ≤ x) (hy : y ≠ 0) : x ^ y = 0 ↔ x = 0 := by
simp [rpow_eq_zero_iff_of_nonneg, *]
@[simp]
lemma rpow_ne_zero (hx : 0 ≤ x) (hy : y ≠ 0) : x ^ y ≠ 0 ↔ x ≠ 0 :=
Real.rpow_eq_zero hx hy |>.not
open Real
theorem rpow_def_of_neg {x : ℝ} (hx : x < 0) (y : ℝ) : x ^ y = exp (log x * y) * cos (y * π) := by
rw [rpow_def, Complex.cpow_def, if_neg]
· have : Complex.log x * y = ↑(log (-x) * y) + ↑(y * π) * Complex.I := by
simp only [Complex.log, Complex.norm_real, norm_eq_abs, abs_of_neg hx, log_neg_eq_log,
Complex.arg_ofReal_of_neg hx, Complex.ofReal_mul]
ring
rw [this, Complex.exp_add_mul_I, ← Complex.ofReal_exp, ← Complex.ofReal_cos, ←
Complex.ofReal_sin, mul_add, ← Complex.ofReal_mul, ← mul_assoc, ← Complex.ofReal_mul,
Complex.add_re, Complex.ofReal_re, Complex.mul_re, Complex.I_re, Complex.ofReal_im,
Real.log_neg_eq_log]
ring
· rw [Complex.ofReal_eq_zero]
exact ne_of_lt hx
theorem rpow_def_of_nonpos {x : ℝ} (hx : x ≤ 0) (y : ℝ) :
x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) * cos (y * π) := by
split_ifs with h <;> simp [rpow_def, *]; exact rpow_def_of_neg (lt_of_le_of_ne hx h) _
@[bound]
theorem rpow_pos_of_pos {x : ℝ} (hx : 0 < x) (y : ℝ) : 0 < x ^ y := by
rw [rpow_def_of_pos hx]; apply exp_pos
@[simp]
theorem rpow_zero (x : ℝ) : x ^ (0 : ℝ) = 1 := by simp [rpow_def]
theorem rpow_zero_pos (x : ℝ) : 0 < x ^ (0 : ℝ) := by simp
@[simp]
theorem zero_rpow {x : ℝ} (h : x ≠ 0) : (0 : ℝ) ^ x = 0 := by simp [rpow_def, *]
theorem zero_rpow_eq_iff {x : ℝ} {a : ℝ} : 0 ^ x = a ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by
constructor
· intro hyp
simp only [rpow_def, Complex.ofReal_zero] at hyp
by_cases h : x = 0
· subst h
simp only [Complex.one_re, Complex.ofReal_zero, Complex.cpow_zero] at hyp
exact Or.inr ⟨rfl, hyp.symm⟩
· rw [Complex.zero_cpow (Complex.ofReal_ne_zero.mpr h)] at hyp
exact Or.inl ⟨h, hyp.symm⟩
· rintro (⟨h, rfl⟩ | ⟨rfl, rfl⟩)
· exact zero_rpow h
· exact rpow_zero _
theorem eq_zero_rpow_iff {x : ℝ} {a : ℝ} : a = 0 ^ x ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by
rw [← zero_rpow_eq_iff, eq_comm]
@[simp]
theorem rpow_one (x : ℝ) : x ^ (1 : ℝ) = x := by simp [rpow_def]
@[simp]
theorem one_rpow (x : ℝ) : (1 : ℝ) ^ x = 1 := by simp [rpow_def]
theorem zero_rpow_le_one (x : ℝ) : (0 : ℝ) ^ x ≤ 1 := by
by_cases h : x = 0 <;> simp [h, zero_le_one]
theorem zero_rpow_nonneg (x : ℝ) : 0 ≤ (0 : ℝ) ^ x := by
by_cases h : x = 0 <;> simp [h, zero_le_one]
@[bound]
theorem rpow_nonneg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) : 0 ≤ x ^ y := by
rw [rpow_def_of_nonneg hx]; split_ifs <;>
simp only [zero_le_one, le_refl, le_of_lt (exp_pos _)]
theorem abs_rpow_of_nonneg {x y : ℝ} (hx_nonneg : 0 ≤ x) : |x ^ y| = |x| ^ y := by
have h_rpow_nonneg : 0 ≤ x ^ y := Real.rpow_nonneg hx_nonneg _
rw [abs_eq_self.mpr hx_nonneg, abs_eq_self.mpr h_rpow_nonneg]
@[bound]
theorem abs_rpow_le_abs_rpow (x y : ℝ) : |x ^ y| ≤ |x| ^ y := by
rcases le_or_lt 0 x with hx | hx
· rw [abs_rpow_of_nonneg hx]
· rw [abs_of_neg hx, rpow_def_of_neg hx, rpow_def_of_pos (neg_pos.2 hx), log_neg_eq_log, abs_mul,
abs_of_pos (exp_pos _)]
exact mul_le_of_le_one_right (exp_pos _).le (abs_cos_le_one _)
theorem abs_rpow_le_exp_log_mul (x y : ℝ) : |x ^ y| ≤ exp (log x * y) := by
refine (abs_rpow_le_abs_rpow x y).trans ?_
by_cases hx : x = 0
· by_cases hy : y = 0 <;> simp [hx, hy, zero_le_one]
· rw [rpow_def_of_pos (abs_pos.2 hx), log_abs]
lemma rpow_inv_log (hx₀ : 0 < x) (hx₁ : x ≠ 1) : x ^ (log x)⁻¹ = exp 1 := by
rw [rpow_def_of_pos hx₀, mul_inv_cancel₀]
exact log_ne_zero.2 ⟨hx₀.ne', hx₁, (hx₀.trans' <| by norm_num).ne'⟩
/-- See `Real.rpow_inv_log` for the equality when `x ≠ 1` is strictly positive. -/
lemma rpow_inv_log_le_exp_one : x ^ (log x)⁻¹ ≤ exp 1 := by
calc
_ ≤ |x ^ (log x)⁻¹| := le_abs_self _
_ ≤ |x| ^ (log x)⁻¹ := abs_rpow_le_abs_rpow ..
rw [← log_abs]
obtain hx | hx := (abs_nonneg x).eq_or_gt
· simp [hx]
· rw [rpow_def_of_pos hx]
gcongr
exact mul_inv_le_one
theorem norm_rpow_of_nonneg {x y : ℝ} (hx_nonneg : 0 ≤ x) : ‖x ^ y‖ = ‖x‖ ^ y := by
simp_rw [Real.norm_eq_abs]
exact abs_rpow_of_nonneg hx_nonneg
variable {w x y z : ℝ}
theorem rpow_add (hx : 0 < x) (y z : ℝ) : x ^ (y + z) = x ^ y * x ^ z := by
simp only [rpow_def_of_pos hx, mul_add, exp_add]
theorem rpow_add' (hx : 0 ≤ x) (h : y + z ≠ 0) : x ^ (y + z) = x ^ y * x ^ z := by
rcases hx.eq_or_lt with (rfl | pos)
· rw [zero_rpow h, zero_eq_mul]
have : y ≠ 0 ∨ z ≠ 0 := not_and_or.1 fun ⟨hy, hz⟩ => h <| hy.symm ▸ hz.symm ▸ zero_add 0
exact this.imp zero_rpow zero_rpow
· exact rpow_add pos _ _
/-- Variant of `Real.rpow_add'` that avoids having to prove `y + z = w` twice. -/
lemma rpow_of_add_eq (hx : 0 ≤ x) (hw : w ≠ 0) (h : y + z = w) : x ^ w = x ^ y * x ^ z := by
rw [← h, rpow_add' hx]; rwa [h]
theorem rpow_add_of_nonneg (hx : 0 ≤ x) (hy : 0 ≤ y) (hz : 0 ≤ z) :
x ^ (y + z) = x ^ y * x ^ z := by
rcases hy.eq_or_lt with (rfl | hy)
· rw [zero_add, rpow_zero, one_mul]
exact rpow_add' hx (ne_of_gt <| add_pos_of_pos_of_nonneg hy hz)
/-- For `0 ≤ x`, the only problematic case in the equality `x ^ y * x ^ z = x ^ (y + z)` is for
`x = 0` and `y + z = 0`, where the right hand side is `1` while the left hand side can vanish.
The inequality is always true, though, and given in this lemma. -/
theorem le_rpow_add {x : ℝ} (hx : 0 ≤ x) (y z : ℝ) : x ^ y * x ^ z ≤ x ^ (y + z) := by
rcases le_iff_eq_or_lt.1 hx with (H | pos)
· by_cases h : y + z = 0
· simp only [H.symm, h, rpow_zero]
calc
(0 : ℝ) ^ y * 0 ^ z ≤ 1 * 1 :=
mul_le_mul (zero_rpow_le_one y) (zero_rpow_le_one z) (zero_rpow_nonneg z) zero_le_one
_ = 1 := by simp
· simp [rpow_add', ← H, h]
· simp [rpow_add pos]
theorem rpow_sum_of_pos {ι : Type*} {a : ℝ} (ha : 0 < a) (f : ι → ℝ) (s : Finset ι) :
(a ^ ∑ x ∈ s, f x) = ∏ x ∈ s, a ^ f x :=
map_sum (⟨⟨fun (x : ℝ) => (a ^ x : ℝ), rpow_zero a⟩, rpow_add ha⟩ : ℝ →+ (Additive ℝ)) f s
theorem rpow_sum_of_nonneg {ι : Type*} {a : ℝ} (ha : 0 ≤ a) {s : Finset ι} {f : ι → ℝ}
(h : ∀ x ∈ s, 0 ≤ f x) : (a ^ ∑ x ∈ s, f x) = ∏ x ∈ s, a ^ f x := by
induction' s using Finset.cons_induction with i s hi ihs
· rw [sum_empty, Finset.prod_empty, rpow_zero]
· rw [forall_mem_cons] at h
rw [sum_cons, prod_cons, ← ihs h.2, rpow_add_of_nonneg ha h.1 (sum_nonneg h.2)]
theorem rpow_neg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) : x ^ (-y) = (x ^ y)⁻¹ := by
simp only [rpow_def_of_nonneg hx]; split_ifs <;> simp_all [exp_neg]
theorem rpow_sub {x : ℝ} (hx : 0 < x) (y z : ℝ) : x ^ (y - z) = x ^ y / x ^ z := by
simp only [sub_eq_add_neg, rpow_add hx, rpow_neg (le_of_lt hx), div_eq_mul_inv]
theorem rpow_sub' {x : ℝ} (hx : 0 ≤ x) {y z : ℝ} (h : y - z ≠ 0) : x ^ (y - z) = x ^ y / x ^ z := by
simp only [sub_eq_add_neg] at h ⊢
simp only [rpow_add' hx h, rpow_neg hx, div_eq_mul_inv]
protected theorem _root_.HasCompactSupport.rpow_const {α : Type*} [TopologicalSpace α] {f : α → ℝ}
(hf : HasCompactSupport f) {r : ℝ} (hr : r ≠ 0) : HasCompactSupport (fun x ↦ f x ^ r) :=
hf.comp_left (g := (· ^ r)) (Real.zero_rpow hr)
end Real
/-!
## Comparing real and complex powers
-/
namespace Complex
theorem ofReal_cpow {x : ℝ} (hx : 0 ≤ x) (y : ℝ) : ((x ^ y : ℝ) : ℂ) = (x : ℂ) ^ (y : ℂ) := by
simp only [Real.rpow_def_of_nonneg hx, Complex.cpow_def, ofReal_eq_zero]; split_ifs <;>
simp [Complex.ofReal_log hx]
theorem ofReal_cpow_of_nonpos {x : ℝ} (hx : x ≤ 0) (y : ℂ) :
(x : ℂ) ^ y = (-x : ℂ) ^ y * exp (π * I * y) := by
rcases hx.eq_or_lt with (rfl | hlt)
· rcases eq_or_ne y 0 with (rfl | hy) <;> simp [*]
have hne : (x : ℂ) ≠ 0 := ofReal_ne_zero.mpr hlt.ne
rw [cpow_def_of_ne_zero hne, cpow_def_of_ne_zero (neg_ne_zero.2 hne), ← exp_add, ← add_mul, log,
log, norm_neg, arg_ofReal_of_neg hlt, ← ofReal_neg, arg_ofReal_of_nonneg (neg_nonneg.2 hx),
ofReal_zero, zero_mul, add_zero]
lemma cpow_ofReal (x : ℂ) (y : ℝ) :
x ^ (y : ℂ) = ↑(‖x‖ ^ y) * (Real.cos (arg x * y) + Real.sin (arg x * y) * I) := by
rcases eq_or_ne x 0 with rfl | hx
· simp [ofReal_cpow le_rfl]
· rw [cpow_def_of_ne_zero hx, exp_eq_exp_re_mul_sin_add_cos, mul_comm (log x)]
norm_cast
rw [re_ofReal_mul, im_ofReal_mul, log_re, log_im, mul_comm y, mul_comm y, Real.exp_mul,
Real.exp_log]
rwa [norm_pos_iff]
lemma cpow_ofReal_re (x : ℂ) (y : ℝ) : (x ^ (y : ℂ)).re = ‖x‖ ^ y * Real.cos (arg x * y) := by
rw [cpow_ofReal]; generalize arg x * y = z; simp [Real.cos]
lemma cpow_ofReal_im (x : ℂ) (y : ℝ) : (x ^ (y : ℂ)).im = ‖x‖ ^ y * Real.sin (arg x * y) := by
rw [cpow_ofReal]; generalize arg x * y = z; simp [Real.sin]
theorem norm_cpow_of_ne_zero {z : ℂ} (hz : z ≠ 0) (w : ℂ) :
‖z ^ w‖ = ‖z‖ ^ w.re / Real.exp (arg z * im w) := by
rw [cpow_def_of_ne_zero hz, norm_exp, mul_re, log_re, log_im, Real.exp_sub,
Real.rpow_def_of_pos (norm_pos_iff.mpr hz)]
theorem norm_cpow_of_imp {z w : ℂ} (h : z = 0 → w.re = 0 → w = 0) :
‖z ^ w‖ = ‖z‖ ^ w.re / Real.exp (arg z * im w) := by
rcases ne_or_eq z 0 with (hz | rfl) <;> [exact norm_cpow_of_ne_zero hz w; rw [norm_zero]]
rcases eq_or_ne w.re 0 with hw | hw
· simp [hw, h rfl hw]
· rw [Real.zero_rpow hw, zero_div, zero_cpow, norm_zero]
exact ne_of_apply_ne re hw
theorem norm_cpow_le (z w : ℂ) : ‖z ^ w‖ ≤ ‖z‖ ^ w.re / Real.exp (arg z * im w) := by
by_cases h : z = 0 → w.re = 0 → w = 0
· exact (norm_cpow_of_imp h).le
· push_neg at h
simp [h]
@[simp]
theorem norm_cpow_real (x : ℂ) (y : ℝ) : ‖x ^ (y : ℂ)‖ = ‖x‖ ^ y := by
rw [norm_cpow_of_imp] <;> simp
@[simp]
theorem norm_cpow_inv_nat (x : ℂ) (n : ℕ) : ‖x ^ (n⁻¹ : ℂ)‖ = ‖x‖ ^ (n⁻¹ : ℝ) := by
rw [← norm_cpow_real]; simp
theorem norm_cpow_eq_rpow_re_of_pos {x : ℝ} (hx : 0 < x) (y : ℂ) : ‖(x : ℂ) ^ y‖ = x ^ y.re := by
rw [norm_cpow_of_ne_zero (ofReal_ne_zero.mpr hx.ne'), arg_ofReal_of_nonneg hx.le,
zero_mul, Real.exp_zero, div_one, Complex.norm_of_nonneg hx.le]
theorem norm_cpow_eq_rpow_re_of_nonneg {x : ℝ} (hx : 0 ≤ x) {y : ℂ} (hy : re y ≠ 0) :
‖(x : ℂ) ^ y‖ = x ^ re y := by
rw [norm_cpow_of_imp] <;> simp [*, arg_ofReal_of_nonneg, abs_of_nonneg]
@[deprecated (since := "2025-02-17")] alias abs_cpow_of_ne_zero := norm_cpow_of_ne_zero
@[deprecated (since := "2025-02-17")] alias abs_cpow_of_imp := norm_cpow_of_imp
@[deprecated (since := "2025-02-17")] alias abs_cpow_le := norm_cpow_le
@[deprecated (since := "2025-02-17")] alias abs_cpow_real := norm_cpow_real
@[deprecated (since := "2025-02-17")] alias abs_cpow_inv_nat := norm_cpow_inv_nat
@[deprecated (since := "2025-02-17")] alias abs_cpow_eq_rpow_re_of_pos :=
norm_cpow_eq_rpow_re_of_pos
@[deprecated (since := "2025-02-17")] alias abs_cpow_eq_rpow_re_of_nonneg :=
norm_cpow_eq_rpow_re_of_nonneg
open Filter in
lemma norm_ofReal_cpow_eventually_eq_atTop (c : ℂ) :
(fun t : ℝ ↦ ‖(t : ℂ) ^ c‖) =ᶠ[atTop] fun t ↦ t ^ c.re := by
filter_upwards [eventually_gt_atTop 0] with t ht
rw [norm_cpow_eq_rpow_re_of_pos ht]
lemma norm_natCast_cpow_of_re_ne_zero (n : ℕ) {s : ℂ} (hs : s.re ≠ 0) :
‖(n : ℂ) ^ s‖ = (n : ℝ) ^ (s.re) := by
rw [← ofReal_natCast, norm_cpow_eq_rpow_re_of_nonneg n.cast_nonneg hs]
lemma norm_natCast_cpow_of_pos {n : ℕ} (hn : 0 < n) (s : ℂ) :
‖(n : ℂ) ^ s‖ = (n : ℝ) ^ (s.re) := by
rw [← ofReal_natCast, norm_cpow_eq_rpow_re_of_pos (Nat.cast_pos.mpr hn) _]
lemma norm_natCast_cpow_pos_of_pos {n : ℕ} (hn : 0 < n) (s : ℂ) : 0 < ‖(n : ℂ) ^ s‖ :=
(norm_natCast_cpow_of_pos hn _).symm ▸ Real.rpow_pos_of_pos (Nat.cast_pos.mpr hn) _
theorem cpow_mul_ofReal_nonneg {x : ℝ} (hx : 0 ≤ x) (y : ℝ) (z : ℂ) :
(x : ℂ) ^ (↑y * z) = (↑(x ^ y) : ℂ) ^ z := by
rw [cpow_mul, ofReal_cpow hx]
· rw [← ofReal_log hx, ← ofReal_mul, ofReal_im, neg_lt_zero]; exact Real.pi_pos
· rw [← ofReal_log hx, ← ofReal_mul, ofReal_im]; exact Real.pi_pos.le
end Complex
/-! ### Positivity extension -/
namespace Mathlib.Meta.Positivity
open Lean Meta Qq
/-- Extension for the `positivity` tactic: exponentiation by a real number is positive (namely 1)
when the exponent is zero. The other cases are done in `evalRpow`. -/
@[positivity (_ : ℝ) ^ (0 : ℝ)]
def evalRpowZero : PositivityExt where eval {u α} _ _ e := do
match u, α, e with
| 0, ~q(ℝ), ~q($a ^ (0 : ℝ)) =>
assertInstancesCommute
pure (.positive q(Real.rpow_zero_pos $a))
| _, _, _ => throwError "not Real.rpow"
/-- Extension for the `positivity` tactic: exponentiation by a real number is nonnegative when
the base is nonnegative and positive when the base is positive. -/
@[positivity (_ : ℝ) ^ (_ : ℝ)]
def evalRpow : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℝ), ~q($a ^ ($b : ℝ)) =>
let ra ← core q(inferInstance) q(inferInstance) a
assertInstancesCommute
match ra with
| .positive pa =>
pure (.positive q(Real.rpow_pos_of_pos $pa $b))
| .nonnegative pa =>
pure (.nonnegative q(Real.rpow_nonneg $pa $b))
| _ => pure .none
| _, _, _ => throwError "not Real.rpow"
end Mathlib.Meta.Positivity
/-!
## Further algebraic properties of `rpow`
-/
namespace Real
variable {x y z : ℝ} {n : ℕ}
theorem rpow_mul {x : ℝ} (hx : 0 ≤ x) (y z : ℝ) : x ^ (y * z) = (x ^ y) ^ z := by
rw [← Complex.ofReal_inj, Complex.ofReal_cpow (rpow_nonneg hx _),
Complex.ofReal_cpow hx, Complex.ofReal_mul, Complex.cpow_mul, Complex.ofReal_cpow hx] <;>
simp only [(Complex.ofReal_mul _ _).symm, (Complex.ofReal_log hx).symm, Complex.ofReal_im,
neg_lt_zero, pi_pos, le_of_lt pi_pos]
lemma rpow_pow_comm {x : ℝ} (hx : 0 ≤ x) (y : ℝ) (n : ℕ) : (x ^ y) ^ n = (x ^ n) ^ y := by
simp_rw [← rpow_natCast, ← rpow_mul hx, mul_comm y]
lemma rpow_zpow_comm {x : ℝ} (hx : 0 ≤ x) (y : ℝ) (n : ℤ) : (x ^ y) ^ n = (x ^ n) ^ y := by
simp_rw [← rpow_intCast, ← rpow_mul hx, mul_comm y]
lemma rpow_add_intCast {x : ℝ} (hx : x ≠ 0) (y : ℝ) (n : ℤ) : x ^ (y + n) = x ^ y * x ^ n := by
rw [rpow_def, rpow_def, Complex.ofReal_add,
Complex.cpow_add _ _ (Complex.ofReal_ne_zero.mpr hx), Complex.ofReal_intCast,
Complex.cpow_intCast, ← Complex.ofReal_zpow, mul_comm, Complex.re_ofReal_mul, mul_comm]
lemma rpow_add_natCast {x : ℝ} (hx : x ≠ 0) (y : ℝ) (n : ℕ) : x ^ (y + n) = x ^ y * x ^ n := by
simpa using rpow_add_intCast hx y n
lemma rpow_sub_intCast {x : ℝ} (hx : x ≠ 0) (y : ℝ) (n : ℕ) : x ^ (y - n) = x ^ y / x ^ n := by
simpa using rpow_add_intCast hx y (-n)
lemma rpow_sub_natCast {x : ℝ} (hx : x ≠ 0) (y : ℝ) (n : ℕ) : x ^ (y - n) = x ^ y / x ^ n := by
simpa using rpow_sub_intCast hx y n
lemma rpow_add_intCast' (hx : 0 ≤ x) {n : ℤ} (h : y + n ≠ 0) : x ^ (y + n) = x ^ y * x ^ n := by
rw [rpow_add' hx h, rpow_intCast]
lemma rpow_add_natCast' (hx : 0 ≤ x) (h : y + n ≠ 0) : x ^ (y + n) = x ^ y * x ^ n := by
rw [rpow_add' hx h, rpow_natCast]
lemma rpow_sub_intCast' (hx : 0 ≤ x) {n : ℤ} (h : y - n ≠ 0) : x ^ (y - n) = x ^ y / x ^ n := by
rw [rpow_sub' hx h, rpow_intCast]
lemma rpow_sub_natCast' (hx : 0 ≤ x) (h : y - n ≠ 0) : x ^ (y - n) = x ^ y / x ^ n := by
rw [rpow_sub' hx h, rpow_natCast]
theorem rpow_add_one {x : ℝ} (hx : x ≠ 0) (y : ℝ) : x ^ (y + 1) = x ^ y * x := by
simpa using rpow_add_natCast hx y 1
theorem rpow_sub_one {x : ℝ} (hx : x ≠ 0) (y : ℝ) : x ^ (y - 1) = x ^ y / x := by
simpa using rpow_sub_natCast hx y 1
lemma rpow_add_one' (hx : 0 ≤ x) (h : y + 1 ≠ 0) : x ^ (y + 1) = x ^ y * x := by
rw [rpow_add' hx h, rpow_one]
lemma rpow_one_add' (hx : 0 ≤ x) (h : 1 + y ≠ 0) : x ^ (1 + y) = x * x ^ y := by
rw [rpow_add' hx h, rpow_one]
lemma rpow_sub_one' (hx : 0 ≤ x) (h : y - 1 ≠ 0) : x ^ (y - 1) = x ^ y / x := by
rw [rpow_sub' hx h, rpow_one]
lemma rpow_one_sub' (hx : 0 ≤ x) (h : 1 - y ≠ 0) : x ^ (1 - y) = x / x ^ y := by
rw [rpow_sub' hx h, rpow_one]
@[simp]
theorem rpow_two (x : ℝ) : x ^ (2 : ℝ) = x ^ 2 := by
rw [← rpow_natCast]
simp only [Nat.cast_ofNat]
theorem rpow_neg_one (x : ℝ) : x ^ (-1 : ℝ) = x⁻¹ := by
suffices H : x ^ ((-1 : ℤ) : ℝ) = x⁻¹ by rwa [Int.cast_neg, Int.cast_one] at H
simp only [rpow_intCast, zpow_one, zpow_neg]
theorem mul_rpow (hx : 0 ≤ x) (hy : 0 ≤ y) : (x * y) ^ z = x ^ z * y ^ z := by
iterate 2 rw [Real.rpow_def_of_nonneg]; split_ifs with h_ifs <;> simp_all
· rw [log_mul ‹_› ‹_›, add_mul, exp_add, rpow_def_of_pos (hy.lt_of_ne' ‹_›)]
all_goals positivity
theorem inv_rpow (hx : 0 ≤ x) (y : ℝ) : x⁻¹ ^ y = (x ^ y)⁻¹ := by
simp only [← rpow_neg_one, ← rpow_mul hx, mul_comm]
theorem div_rpow (hx : 0 ≤ x) (hy : 0 ≤ y) (z : ℝ) : (x / y) ^ z = x ^ z / y ^ z := by
simp only [div_eq_mul_inv, mul_rpow hx (inv_nonneg.2 hy), inv_rpow hy]
theorem log_rpow {x : ℝ} (hx : 0 < x) (y : ℝ) : log (x ^ y) = y * log x := by
apply exp_injective
rw [exp_log (rpow_pos_of_pos hx y), ← exp_log hx, mul_comm, rpow_def_of_pos (exp_pos (log x)) y]
theorem mul_log_eq_log_iff {x y z : ℝ} (hx : 0 < x) (hz : 0 < z) :
y * log x = log z ↔ x ^ y = z :=
⟨fun h ↦ log_injOn_pos (rpow_pos_of_pos hx _) hz <| log_rpow hx _ |>.trans h,
by rintro rfl; rw [log_rpow hx]⟩
@[simp] lemma rpow_rpow_inv (hx : 0 ≤ x) (hy : y ≠ 0) : (x ^ y) ^ y⁻¹ = x := by
rw [← rpow_mul hx, mul_inv_cancel₀ hy, rpow_one]
@[simp] lemma rpow_inv_rpow (hx : 0 ≤ x) (hy : y ≠ 0) : (x ^ y⁻¹) ^ y = x := by
rw [← rpow_mul hx, inv_mul_cancel₀ hy, rpow_one]
theorem pow_rpow_inv_natCast (hx : 0 ≤ x) (hn : n ≠ 0) : (x ^ n) ^ (n⁻¹ : ℝ) = x := by
have hn0 : (n : ℝ) ≠ 0 := Nat.cast_ne_zero.2 hn
rw [← rpow_natCast, ← rpow_mul hx, mul_inv_cancel₀ hn0, rpow_one]
| Mathlib/Analysis/SpecialFunctions/Pow/Real.lean | 488 | 489 | theorem rpow_inv_natCast_pow (hx : 0 ≤ x) (hn : n ≠ 0) : (x ^ (n⁻¹ : ℝ)) ^ n = x := by | have hn0 : (n : ℝ) ≠ 0 := Nat.cast_ne_zero.2 hn |
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Johannes Hölzl, Patrick Massot
-/
import Mathlib.Data.Set.Image
import Mathlib.Data.SProd
/-!
# Sets in product and pi types
This file proves basic properties of product of sets in `α × β` and in `Π i, α i`, and of the
diagonal of a type.
## Main declarations
This file contains basic results on the following notions, which are defined in `Set.Operations`.
* `Set.prod`: Binary product of sets. For `s : Set α`, `t : Set β`, we have
`s.prod t : Set (α × β)`. Denoted by `s ×ˢ t`.
* `Set.diagonal`: Diagonal of a type. `Set.diagonal α = {(x, x) | x : α}`.
* `Set.offDiag`: Off-diagonal. `s ×ˢ s` without the diagonal.
* `Set.pi`: Arbitrary product of sets.
-/
open Function
namespace Set
/-! ### Cartesian binary product of sets -/
section Prod
variable {α β γ δ : Type*} {s s₁ s₂ : Set α} {t t₁ t₂ : Set β} {a : α} {b : β}
theorem Subsingleton.prod (hs : s.Subsingleton) (ht : t.Subsingleton) :
(s ×ˢ t).Subsingleton := fun _x hx _y hy ↦
Prod.ext (hs hx.1 hy.1) (ht hx.2 hy.2)
noncomputable instance decidableMemProd [DecidablePred (· ∈ s)] [DecidablePred (· ∈ t)] :
DecidablePred (· ∈ s ×ˢ t) := fun x => inferInstanceAs (Decidable (x.1 ∈ s ∧ x.2 ∈ t))
@[gcongr]
theorem prod_mono (hs : s₁ ⊆ s₂) (ht : t₁ ⊆ t₂) : s₁ ×ˢ t₁ ⊆ s₂ ×ˢ t₂ :=
fun _ ⟨h₁, h₂⟩ => ⟨hs h₁, ht h₂⟩
@[gcongr]
theorem prod_mono_left (hs : s₁ ⊆ s₂) : s₁ ×ˢ t ⊆ s₂ ×ˢ t :=
prod_mono hs Subset.rfl
@[gcongr]
theorem prod_mono_right (ht : t₁ ⊆ t₂) : s ×ˢ t₁ ⊆ s ×ˢ t₂ :=
prod_mono Subset.rfl ht
@[simp]
theorem prod_self_subset_prod_self : s₁ ×ˢ s₁ ⊆ s₂ ×ˢ s₂ ↔ s₁ ⊆ s₂ :=
⟨fun h _ hx => (h (mk_mem_prod hx hx)).1, fun h _ hx => ⟨h hx.1, h hx.2⟩⟩
@[simp]
theorem prod_self_ssubset_prod_self : s₁ ×ˢ s₁ ⊂ s₂ ×ˢ s₂ ↔ s₁ ⊂ s₂ :=
and_congr prod_self_subset_prod_self <| not_congr prod_self_subset_prod_self
theorem prod_subset_iff {P : Set (α × β)} : s ×ˢ t ⊆ P ↔ ∀ x ∈ s, ∀ y ∈ t, (x, y) ∈ P :=
⟨fun h _ hx _ hy => h (mk_mem_prod hx hy), fun h ⟨_, _⟩ hp => h _ hp.1 _ hp.2⟩
theorem forall_prod_set {p : α × β → Prop} : (∀ x ∈ s ×ˢ t, p x) ↔ ∀ x ∈ s, ∀ y ∈ t, p (x, y) :=
prod_subset_iff
theorem exists_prod_set {p : α × β → Prop} : (∃ x ∈ s ×ˢ t, p x) ↔ ∃ x ∈ s, ∃ y ∈ t, p (x, y) := by
simp [and_assoc]
@[simp]
theorem prod_empty : s ×ˢ (∅ : Set β) = ∅ := by
ext
exact iff_of_eq (and_false _)
@[simp]
theorem empty_prod : (∅ : Set α) ×ˢ t = ∅ := by
ext
exact iff_of_eq (false_and _)
@[simp, mfld_simps]
theorem univ_prod_univ : @univ α ×ˢ @univ β = univ := by
ext
exact iff_of_eq (true_and _)
theorem univ_prod {t : Set β} : (univ : Set α) ×ˢ t = Prod.snd ⁻¹' t := by simp [prod_eq]
theorem prod_univ {s : Set α} : s ×ˢ (univ : Set β) = Prod.fst ⁻¹' s := by simp [prod_eq]
@[simp] lemma prod_eq_univ [Nonempty α] [Nonempty β] : s ×ˢ t = univ ↔ s = univ ∧ t = univ := by
simp [eq_univ_iff_forall, forall_and]
| Mathlib/Data/Set/Prod.lean | 96 | 98 | theorem singleton_prod : ({a} : Set α) ×ˢ t = Prod.mk a '' t := by | ext ⟨x, y⟩
simp [and_left_comm, eq_comm] |
/-
Copyright (c) 2020 Kexing Ying and Kevin Buzzard. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying, Kevin Buzzard, Yury Kudryashov
-/
import Mathlib.Algebra.BigOperators.GroupWithZero.Finset
import Mathlib.Algebra.BigOperators.Pi
import Mathlib.Algebra.Group.FiniteSupport
import Mathlib.Algebra.NoZeroSMulDivisors.Basic
import Mathlib.Algebra.Order.BigOperators.Group.Finset
import Mathlib.Algebra.Order.Ring.Defs
import Mathlib.Data.Set.Finite.Lattice
import Mathlib.Data.Set.Subsingleton
/-!
# Finite products and sums over types and sets
We define products and sums over types and subsets of types, with no finiteness hypotheses.
All infinite products and sums are defined to be junk values (i.e. one or zero).
This approach is sometimes easier to use than `Finset.sum`,
when issues arise with `Finset` and `Fintype` being data.
## Main definitions
We use the following variables:
* `α`, `β` - types with no structure;
* `s`, `t` - sets
* `M`, `N` - additive or multiplicative commutative monoids
* `f`, `g` - functions
Definitions in this file:
* `finsum f : M` : the sum of `f x` as `x` ranges over the support of `f`, if it's finite.
Zero otherwise.
* `finprod f : M` : the product of `f x` as `x` ranges over the multiplicative support of `f`, if
it's finite. One otherwise.
## Notation
* `∑ᶠ i, f i` and `∑ᶠ i : α, f i` for `finsum f`
* `∏ᶠ i, f i` and `∏ᶠ i : α, f i` for `finprod f`
This notation works for functions `f : p → M`, where `p : Prop`, so the following works:
* `∑ᶠ i ∈ s, f i`, where `f : α → M`, `s : Set α` : sum over the set `s`;
* `∑ᶠ n < 5, f n`, where `f : ℕ → M` : same as `f 0 + f 1 + f 2 + f 3 + f 4`;
* `∏ᶠ (n >= -2) (hn : n < 3), f n`, where `f : ℤ → M` : same as `f (-2) * f (-1) * f 0 * f 1 * f 2`.
## Implementation notes
`finsum` and `finprod` is "yet another way of doing finite sums and products in Lean". However
experiments in the wild (e.g. with matroids) indicate that it is a helpful approach in settings
where the user is not interested in computability and wants to do reasoning without running into
typeclass diamonds caused by the constructive finiteness used in definitions such as `Finset` and
`Fintype`. By sticking solely to `Set.Finite` we avoid these problems. We are aware that there are
other solutions but for beginner mathematicians this approach is easier in practice.
Another application is the construction of a partition of unity from a collection of “bump”
function. In this case the finite set depends on the point and it's convenient to have a definition
that does not mention the set explicitly.
The first arguments in all definitions and lemmas is the codomain of the function of the big
operator. This is necessary for the heuristic in `@[to_additive]`.
See the documentation of `to_additive.attr` for more information.
We did not add `IsFinite (X : Type) : Prop`, because it is simply `Nonempty (Fintype X)`.
## Tags
finsum, finprod, finite sum, finite product
-/
open Function Set
/-!
### Definition and relation to `Finset.sum` and `Finset.prod`
-/
-- Porting note: Used to be section Sort
section sort
variable {G M N : Type*} {α β ι : Sort*} [CommMonoid M] [CommMonoid N]
section
/- Note: we use classical logic only for these definitions, to ensure that we do not write lemmas
with `Classical.dec` in their statement. -/
open Classical in
/-- Sum of `f x` as `x` ranges over the elements of the support of `f`, if it's finite. Zero
otherwise. -/
noncomputable irreducible_def finsum (lemma := finsum_def') [AddCommMonoid M] (f : α → M) : M :=
if h : (support (f ∘ PLift.down)).Finite then ∑ i ∈ h.toFinset, f i.down else 0
open Classical in
/-- Product of `f x` as `x` ranges over the elements of the multiplicative support of `f`, if it's
finite. One otherwise. -/
@[to_additive existing]
noncomputable irreducible_def finprod (lemma := finprod_def') (f : α → M) : M :=
if h : (mulSupport (f ∘ PLift.down)).Finite then ∏ i ∈ h.toFinset, f i.down else 1
attribute [to_additive existing] finprod_def'
end
open Batteries.ExtendedBinder
/-- `∑ᶠ x, f x` is notation for `finsum f`. It is the sum of `f x`, where `x` ranges over the
support of `f`, if it's finite, zero otherwise. Taking the sum over multiple arguments or
conditions is possible, e.g. `∏ᶠ (x) (y), f x y` and `∏ᶠ (x) (h: x ∈ s), f x` -/
notation3"∑ᶠ "(...)", "r:67:(scoped f => finsum f) => r
/-- `∏ᶠ x, f x` is notation for `finprod f`. It is the product of `f x`, where `x` ranges over the
multiplicative support of `f`, if it's finite, one otherwise. Taking the product over multiple
arguments or conditions is possible, e.g. `∏ᶠ (x) (y), f x y` and `∏ᶠ (x) (h: x ∈ s), f x` -/
notation3"∏ᶠ "(...)", "r:67:(scoped f => finprod f) => r
-- Porting note: The following ports the lean3 notation for this file, but is currently very fickle.
-- syntax (name := bigfinsum) "∑ᶠ" extBinders ", " term:67 : term
-- macro_rules (kind := bigfinsum)
-- | `(∑ᶠ $x:ident, $p) => `(finsum (fun $x:ident ↦ $p))
-- | `(∑ᶠ $x:ident : $t, $p) => `(finsum (fun $x:ident : $t ↦ $p))
-- | `(∑ᶠ $x:ident $b:binderPred, $p) =>
-- `(finsum fun $x => (finsum (α := satisfies_binder_pred% $x $b) (fun _ => $p)))
-- | `(∑ᶠ ($x:ident) ($h:ident : $t), $p) =>
-- `(finsum fun ($x) => finsum (α := $t) (fun $h => $p))
-- | `(∑ᶠ ($x:ident : $_) ($h:ident : $t), $p) =>
-- `(finsum fun ($x) => finsum (α := $t) (fun $h => $p))
-- | `(∑ᶠ ($x:ident) ($y:ident), $p) =>
-- `(finsum fun $x => (finsum fun $y => $p))
-- | `(∑ᶠ ($x:ident) ($y:ident) ($h:ident : $t), $p) =>
-- `(finsum fun $x => (finsum fun $y => (finsum (α := $t) fun $h => $p)))
-- | `(∑ᶠ ($x:ident) ($y:ident) ($z:ident), $p) =>
-- `(finsum fun $x => (finsum fun $y => (finsum fun $z => $p)))
-- | `(∑ᶠ ($x:ident) ($y:ident) ($z:ident) ($h:ident : $t), $p) =>
-- `(finsum fun $x => (finsum fun $y => (finsum fun $z => (finsum (α := $t) fun $h => $p))))
--
--
-- syntax (name := bigfinprod) "∏ᶠ " extBinders ", " term:67 : term
-- macro_rules (kind := bigfinprod)
-- | `(∏ᶠ $x:ident, $p) => `(finprod (fun $x:ident ↦ $p))
-- | `(∏ᶠ $x:ident : $t, $p) => `(finprod (fun $x:ident : $t ↦ $p))
-- | `(∏ᶠ $x:ident $b:binderPred, $p) =>
-- `(finprod fun $x => (finprod (α := satisfies_binder_pred% $x $b) (fun _ => $p)))
-- | `(∏ᶠ ($x:ident) ($h:ident : $t), $p) =>
-- `(finprod fun ($x) => finprod (α := $t) (fun $h => $p))
-- | `(∏ᶠ ($x:ident : $_) ($h:ident : $t), $p) =>
-- `(finprod fun ($x) => finprod (α := $t) (fun $h => $p))
-- | `(∏ᶠ ($x:ident) ($y:ident), $p) =>
-- `(finprod fun $x => (finprod fun $y => $p))
-- | `(∏ᶠ ($x:ident) ($y:ident) ($h:ident : $t), $p) =>
-- `(finprod fun $x => (finprod fun $y => (finprod (α := $t) fun $h => $p)))
-- | `(∏ᶠ ($x:ident) ($y:ident) ($z:ident), $p) =>
-- `(finprod fun $x => (finprod fun $y => (finprod fun $z => $p)))
-- | `(∏ᶠ ($x:ident) ($y:ident) ($z:ident) ($h:ident : $t), $p) =>
-- `(finprod fun $x => (finprod fun $y => (finprod fun $z =>
-- (finprod (α := $t) fun $h => $p))))
@[to_additive]
theorem finprod_eq_prod_plift_of_mulSupport_toFinset_subset {f : α → M}
(hf : (mulSupport (f ∘ PLift.down)).Finite) {s : Finset (PLift α)} (hs : hf.toFinset ⊆ s) :
∏ᶠ i, f i = ∏ i ∈ s, f i.down := by
rw [finprod, dif_pos]
refine Finset.prod_subset hs fun x _ hxf => ?_
rwa [hf.mem_toFinset, nmem_mulSupport] at hxf
@[to_additive]
theorem finprod_eq_prod_plift_of_mulSupport_subset {f : α → M} {s : Finset (PLift α)}
(hs : mulSupport (f ∘ PLift.down) ⊆ s) : ∏ᶠ i, f i = ∏ i ∈ s, f i.down :=
finprod_eq_prod_plift_of_mulSupport_toFinset_subset (s.finite_toSet.subset hs) fun x hx => by
rw [Finite.mem_toFinset] at hx
exact hs hx
@[to_additive (attr := simp)]
theorem finprod_one : (∏ᶠ _ : α, (1 : M)) = 1 := by
have : (mulSupport fun x : PLift α => (fun _ => 1 : α → M) x.down) ⊆ (∅ : Finset (PLift α)) :=
fun x h => by simp at h
rw [finprod_eq_prod_plift_of_mulSupport_subset this, Finset.prod_empty]
@[to_additive]
theorem finprod_of_isEmpty [IsEmpty α] (f : α → M) : ∏ᶠ i, f i = 1 := by
rw [← finprod_one]
congr
simp [eq_iff_true_of_subsingleton]
@[to_additive (attr := simp)]
theorem finprod_false (f : False → M) : ∏ᶠ i, f i = 1 :=
finprod_of_isEmpty _
@[to_additive]
theorem finprod_eq_single (f : α → M) (a : α) (ha : ∀ x, x ≠ a → f x = 1) :
∏ᶠ x, f x = f a := by
have : mulSupport (f ∘ PLift.down) ⊆ ({PLift.up a} : Finset (PLift α)) := by
intro x
contrapose
simpa [PLift.eq_up_iff_down_eq] using ha x.down
rw [finprod_eq_prod_plift_of_mulSupport_subset this, Finset.prod_singleton]
@[to_additive]
theorem finprod_unique [Unique α] (f : α → M) : ∏ᶠ i, f i = f default :=
finprod_eq_single f default fun _x hx => (hx <| Unique.eq_default _).elim
@[to_additive (attr := simp)]
theorem finprod_true (f : True → M) : ∏ᶠ i, f i = f trivial :=
@finprod_unique M True _ ⟨⟨trivial⟩, fun _ => rfl⟩ f
@[to_additive]
theorem finprod_eq_dif {p : Prop} [Decidable p] (f : p → M) :
∏ᶠ i, f i = if h : p then f h else 1 := by
split_ifs with h
· haveI : Unique p := ⟨⟨h⟩, fun _ => rfl⟩
exact finprod_unique f
· haveI : IsEmpty p := ⟨h⟩
exact finprod_of_isEmpty f
@[to_additive]
theorem finprod_eq_if {p : Prop} [Decidable p] {x : M} : ∏ᶠ _ : p, x = if p then x else 1 :=
finprod_eq_dif fun _ => x
@[to_additive]
theorem finprod_congr {f g : α → M} (h : ∀ x, f x = g x) : finprod f = finprod g :=
congr_arg _ <| funext h
@[to_additive (attr := congr)]
theorem finprod_congr_Prop {p q : Prop} {f : p → M} {g : q → M} (hpq : p = q)
(hfg : ∀ h : q, f (hpq.mpr h) = g h) : finprod f = finprod g := by
subst q
exact finprod_congr hfg
/-- To prove a property of a finite product, it suffices to prove that the property is
multiplicative and holds on the factors. -/
@[to_additive
"To prove a property of a finite sum, it suffices to prove that the property is
additive and holds on the summands."]
theorem finprod_induction {f : α → M} (p : M → Prop) (hp₀ : p 1)
(hp₁ : ∀ x y, p x → p y → p (x * y)) (hp₂ : ∀ i, p (f i)) : p (∏ᶠ i, f i) := by
rw [finprod]
split_ifs
exacts [Finset.prod_induction _ _ hp₁ hp₀ fun i _ => hp₂ _, hp₀]
theorem finprod_nonneg {R : Type*} [CommSemiring R] [PartialOrder R] [IsOrderedRing R]
{f : α → R} (hf : ∀ x, 0 ≤ f x) :
0 ≤ ∏ᶠ x, f x :=
finprod_induction (fun x => 0 ≤ x) zero_le_one (fun _ _ => mul_nonneg) hf
@[to_additive finsum_nonneg]
theorem one_le_finprod' {M : Type*} [CommMonoid M] [PartialOrder M] [IsOrderedMonoid M]
{f : α → M} (hf : ∀ i, 1 ≤ f i) :
1 ≤ ∏ᶠ i, f i :=
finprod_induction _ le_rfl (fun _ _ => one_le_mul) hf
@[to_additive]
theorem MonoidHom.map_finprod_plift (f : M →* N) (g : α → M)
(h : (mulSupport <| g ∘ PLift.down).Finite) : f (∏ᶠ x, g x) = ∏ᶠ x, f (g x) := by
rw [finprod_eq_prod_plift_of_mulSupport_subset h.coe_toFinset.ge,
finprod_eq_prod_plift_of_mulSupport_subset, map_prod]
rw [h.coe_toFinset]
exact mulSupport_comp_subset f.map_one (g ∘ PLift.down)
@[to_additive]
theorem MonoidHom.map_finprod_Prop {p : Prop} (f : M →* N) (g : p → M) :
f (∏ᶠ x, g x) = ∏ᶠ x, f (g x) :=
f.map_finprod_plift g (Set.toFinite _)
@[to_additive]
theorem MonoidHom.map_finprod_of_preimage_one (f : M →* N) (hf : ∀ x, f x = 1 → x = 1) (g : α → M) :
f (∏ᶠ i, g i) = ∏ᶠ i, f (g i) := by
by_cases hg : (mulSupport <| g ∘ PLift.down).Finite; · exact f.map_finprod_plift g hg
rw [finprod, dif_neg, f.map_one, finprod, dif_neg]
exacts [Infinite.mono (fun x hx => mt (hf (g x.down)) hx) hg, hg]
@[to_additive]
theorem MonoidHom.map_finprod_of_injective (g : M →* N) (hg : Injective g) (f : α → M) :
g (∏ᶠ i, f i) = ∏ᶠ i, g (f i) :=
g.map_finprod_of_preimage_one (fun _ => (hg.eq_iff' g.map_one).mp) f
@[to_additive]
theorem MulEquiv.map_finprod (g : M ≃* N) (f : α → M) : g (∏ᶠ i, f i) = ∏ᶠ i, g (f i) :=
g.toMonoidHom.map_finprod_of_injective (EquivLike.injective g) f
@[to_additive]
theorem MulEquivClass.map_finprod {F : Type*} [EquivLike F M N] [MulEquivClass F M N] (g : F)
(f : α → M) : g (∏ᶠ i, f i) = ∏ᶠ i, g (f i) :=
MulEquiv.map_finprod (MulEquivClass.toMulEquiv g) f
/-- The `NoZeroSMulDivisors` makes sure that the result holds even when the support of `f` is
infinite. For a more usual version assuming `(support f).Finite` instead, see `finsum_smul'`. -/
theorem finsum_smul {R M : Type*} [Ring R] [AddCommGroup M] [Module R M] [NoZeroSMulDivisors R M]
(f : ι → R) (x : M) : (∑ᶠ i, f i) • x = ∑ᶠ i, f i • x := by
rcases eq_or_ne x 0 with (rfl | hx)
· simp
· exact ((smulAddHom R M).flip x).map_finsum_of_injective (smul_left_injective R hx) _
/-- The `NoZeroSMulDivisors` makes sure that the result holds even when the support of `f` is
infinite. For a more usual version assuming `(support f).Finite` instead, see `smul_finsum'`. -/
theorem smul_finsum {R M : Type*} [Semiring R] [AddCommGroup M] [Module R M]
[NoZeroSMulDivisors R M] (c : R) (f : ι → M) : (c • ∑ᶠ i, f i) = ∑ᶠ i, c • f i := by
rcases eq_or_ne c 0 with (rfl | hc)
· simp
· exact (smulAddHom R M c).map_finsum_of_injective (smul_right_injective M hc) _
@[to_additive]
theorem finprod_inv_distrib [DivisionCommMonoid G] (f : α → G) : (∏ᶠ x, (f x)⁻¹) = (∏ᶠ x, f x)⁻¹ :=
((MulEquiv.inv G).map_finprod f).symm
end sort
-- Porting note: Used to be section Type
section type
variable {α β ι G M N : Type*} [CommMonoid M] [CommMonoid N]
@[to_additive]
theorem finprod_eq_mulIndicator_apply (s : Set α) (f : α → M) (a : α) :
∏ᶠ _ : a ∈ s, f a = mulIndicator s f a := by
classical convert finprod_eq_if (M := M) (p := a ∈ s) (x := f a)
@[to_additive (attr := simp)]
theorem finprod_apply_ne_one (f : α → M) (a : α) : ∏ᶠ _ : f a ≠ 1, f a = f a := by
rw [← mem_mulSupport, finprod_eq_mulIndicator_apply, mulIndicator_mulSupport]
@[to_additive]
theorem finprod_mem_def (s : Set α) (f : α → M) : ∏ᶠ a ∈ s, f a = ∏ᶠ a, mulIndicator s f a :=
finprod_congr <| finprod_eq_mulIndicator_apply s f
@[to_additive]
lemma finprod_mem_mulSupport (f : α → M) : ∏ᶠ a ∈ mulSupport f, f a = ∏ᶠ a, f a := by
rw [finprod_mem_def, mulIndicator_mulSupport]
@[to_additive]
theorem finprod_eq_prod_of_mulSupport_subset (f : α → M) {s : Finset α} (h : mulSupport f ⊆ s) :
∏ᶠ i, f i = ∏ i ∈ s, f i := by
have A : mulSupport (f ∘ PLift.down) = Equiv.plift.symm '' mulSupport f := by
rw [mulSupport_comp_eq_preimage]
exact (Equiv.plift.symm.image_eq_preimage _).symm
have : mulSupport (f ∘ PLift.down) ⊆ s.map Equiv.plift.symm.toEmbedding := by
rw [A, Finset.coe_map]
exact image_subset _ h
rw [finprod_eq_prod_plift_of_mulSupport_subset this]
simp only [Finset.prod_map, Equiv.coe_toEmbedding]
congr
@[to_additive]
theorem finprod_eq_prod_of_mulSupport_toFinset_subset (f : α → M) (hf : (mulSupport f).Finite)
{s : Finset α} (h : hf.toFinset ⊆ s) : ∏ᶠ i, f i = ∏ i ∈ s, f i :=
finprod_eq_prod_of_mulSupport_subset _ fun _ hx => h <| hf.mem_toFinset.2 hx
@[to_additive]
theorem finprod_eq_finset_prod_of_mulSupport_subset (f : α → M) {s : Finset α}
(h : mulSupport f ⊆ (s : Set α)) : ∏ᶠ i, f i = ∏ i ∈ s, f i :=
haveI h' : (s.finite_toSet.subset h).toFinset ⊆ s := by
simpa [← Finset.coe_subset, Set.coe_toFinset]
finprod_eq_prod_of_mulSupport_toFinset_subset _ _ h'
@[to_additive]
theorem finprod_def (f : α → M) [Decidable (mulSupport f).Finite] :
∏ᶠ i : α, f i = if h : (mulSupport f).Finite then ∏ i ∈ h.toFinset, f i else 1 := by
split_ifs with h
· exact finprod_eq_prod_of_mulSupport_toFinset_subset _ h (Finset.Subset.refl _)
· rw [finprod, dif_neg]
rw [mulSupport_comp_eq_preimage]
exact mt (fun hf => hf.of_preimage Equiv.plift.surjective) h
@[to_additive]
theorem finprod_of_infinite_mulSupport {f : α → M} (hf : (mulSupport f).Infinite) :
∏ᶠ i, f i = 1 := by classical rw [finprod_def, dif_neg hf]
@[to_additive]
theorem finprod_eq_prod (f : α → M) (hf : (mulSupport f).Finite) :
∏ᶠ i : α, f i = ∏ i ∈ hf.toFinset, f i := by classical rw [finprod_def, dif_pos hf]
@[to_additive]
theorem finprod_eq_prod_of_fintype [Fintype α] (f : α → M) : ∏ᶠ i : α, f i = ∏ i, f i :=
finprod_eq_prod_of_mulSupport_toFinset_subset _ (Set.toFinite _) <| Finset.subset_univ _
@[to_additive]
theorem map_finset_prod {α F : Type*} [Fintype α] [EquivLike F M N] [MulEquivClass F M N] (f : F)
(g : α → M) : f (∏ i : α, g i) = ∏ i : α, f (g i) := by
simp [← finprod_eq_prod_of_fintype, MulEquivClass.map_finprod]
@[to_additive]
theorem finprod_cond_eq_prod_of_cond_iff (f : α → M) {p : α → Prop} {t : Finset α}
(h : ∀ {x}, f x ≠ 1 → (p x ↔ x ∈ t)) : (∏ᶠ (i) (_ : p i), f i) = ∏ i ∈ t, f i := by
set s := { x | p x }
change ∏ᶠ (i : α) (_ : i ∈ s), f i = ∏ i ∈ t, f i
have : mulSupport (s.mulIndicator f) ⊆ t := by
rw [Set.mulSupport_mulIndicator]
intro x hx
exact (h hx.2).1 hx.1
rw [finprod_mem_def, finprod_eq_prod_of_mulSupport_subset _ this]
refine Finset.prod_congr rfl fun x hx => mulIndicator_apply_eq_self.2 fun hxs => ?_
contrapose! hxs
exact (h hxs).2 hx
@[to_additive]
theorem finprod_cond_ne (f : α → M) (a : α) [DecidableEq α] (hf : (mulSupport f).Finite) :
(∏ᶠ (i) (_ : i ≠ a), f i) = ∏ i ∈ hf.toFinset.erase a, f i := by
apply finprod_cond_eq_prod_of_cond_iff
intro x hx
rw [Finset.mem_erase, Finite.mem_toFinset, mem_mulSupport]
exact ⟨fun h => And.intro h hx, fun h => h.1⟩
@[to_additive]
theorem finprod_mem_eq_prod_of_inter_mulSupport_eq (f : α → M) {s : Set α} {t : Finset α}
(h : s ∩ mulSupport f = t.toSet ∩ mulSupport f) : ∏ᶠ i ∈ s, f i = ∏ i ∈ t, f i :=
finprod_cond_eq_prod_of_cond_iff _ <| by
intro x hxf
rw [← mem_mulSupport] at hxf
refine ⟨fun hx => ?_, fun hx => ?_⟩
· refine ((mem_inter_iff x t (mulSupport f)).mp ?_).1
rw [← Set.ext_iff.mp h x, mem_inter_iff]
exact ⟨hx, hxf⟩
· refine ((mem_inter_iff x s (mulSupport f)).mp ?_).1
rw [Set.ext_iff.mp h x, mem_inter_iff]
exact ⟨hx, hxf⟩
@[to_additive]
theorem finprod_mem_eq_prod_of_subset (f : α → M) {s : Set α} {t : Finset α}
(h₁ : s ∩ mulSupport f ⊆ t) (h₂ : ↑t ⊆ s) : ∏ᶠ i ∈ s, f i = ∏ i ∈ t, f i :=
finprod_cond_eq_prod_of_cond_iff _ fun hx => ⟨fun h => h₁ ⟨h, hx⟩, fun h => h₂ h⟩
@[to_additive]
theorem finprod_mem_eq_prod (f : α → M) {s : Set α} (hf : (s ∩ mulSupport f).Finite) :
∏ᶠ i ∈ s, f i = ∏ i ∈ hf.toFinset, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ <| by simp [inter_assoc]
@[to_additive]
theorem finprod_mem_eq_prod_filter (f : α → M) (s : Set α) [DecidablePred (· ∈ s)]
(hf : (mulSupport f).Finite) :
∏ᶠ i ∈ s, f i = ∏ i ∈ hf.toFinset with i ∈ s, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ <| by
ext x
simp [and_comm]
@[to_additive]
theorem finprod_mem_eq_toFinset_prod (f : α → M) (s : Set α) [Fintype s] :
∏ᶠ i ∈ s, f i = ∏ i ∈ s.toFinset, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ <| by simp_rw [coe_toFinset s]
@[to_additive]
theorem finprod_mem_eq_finite_toFinset_prod (f : α → M) {s : Set α} (hs : s.Finite) :
∏ᶠ i ∈ s, f i = ∏ i ∈ hs.toFinset, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ <| by rw [hs.coe_toFinset]
@[to_additive]
theorem finprod_mem_finset_eq_prod (f : α → M) (s : Finset α) : ∏ᶠ i ∈ s, f i = ∏ i ∈ s, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ rfl
@[to_additive]
theorem finprod_mem_coe_finset (f : α → M) (s : Finset α) :
(∏ᶠ i ∈ (s : Set α), f i) = ∏ i ∈ s, f i :=
finprod_mem_eq_prod_of_inter_mulSupport_eq _ rfl
@[to_additive]
theorem finprod_mem_eq_one_of_infinite {f : α → M} {s : Set α} (hs : (s ∩ mulSupport f).Infinite) :
∏ᶠ i ∈ s, f i = 1 := by
rw [finprod_mem_def]
apply finprod_of_infinite_mulSupport
rwa [← mulSupport_mulIndicator] at hs
@[to_additive]
theorem finprod_mem_eq_one_of_forall_eq_one {f : α → M} {s : Set α} (h : ∀ x ∈ s, f x = 1) :
∏ᶠ i ∈ s, f i = 1 := by simp +contextual [h]
@[to_additive]
theorem finprod_mem_inter_mulSupport (f : α → M) (s : Set α) :
∏ᶠ i ∈ s ∩ mulSupport f, f i = ∏ᶠ i ∈ s, f i := by
rw [finprod_mem_def, finprod_mem_def, mulIndicator_inter_mulSupport]
@[to_additive]
theorem finprod_mem_inter_mulSupport_eq (f : α → M) (s t : Set α)
(h : s ∩ mulSupport f = t ∩ mulSupport f) : ∏ᶠ i ∈ s, f i = ∏ᶠ i ∈ t, f i := by
rw [← finprod_mem_inter_mulSupport, h, finprod_mem_inter_mulSupport]
@[to_additive]
theorem finprod_mem_inter_mulSupport_eq' (f : α → M) (s t : Set α)
(h : ∀ x ∈ mulSupport f, x ∈ s ↔ x ∈ t) : ∏ᶠ i ∈ s, f i = ∏ᶠ i ∈ t, f i := by
apply finprod_mem_inter_mulSupport_eq
ext x
exact and_congr_left (h x)
@[to_additive]
theorem finprod_mem_univ (f : α → M) : ∏ᶠ i ∈ @Set.univ α, f i = ∏ᶠ i : α, f i :=
finprod_congr fun _ => finprod_true _
variable {f g : α → M} {a b : α} {s t : Set α}
@[to_additive]
theorem finprod_mem_congr (h₀ : s = t) (h₁ : ∀ x ∈ t, f x = g x) :
∏ᶠ i ∈ s, f i = ∏ᶠ i ∈ t, g i :=
h₀.symm ▸ finprod_congr fun i => finprod_congr_Prop rfl (h₁ i)
@[to_additive]
| Mathlib/Algebra/BigOperators/Finprod.lean | 505 | 507 | theorem finprod_eq_one_of_forall_eq_one {f : α → M} (h : ∀ x, f x = 1) : ∏ᶠ i, f i = 1 := by | simp +contextual [h] |
/-
Copyright (c) 2023 Xavier Roblot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Xavier Roblot
-/
import Mathlib.Data.Complex.FiniteDimensional
import Mathlib.MeasureTheory.Constructions.HaarToSphere
import Mathlib.MeasureTheory.Integral.Gamma
import Mathlib.MeasureTheory.Integral.Pi
import Mathlib.Analysis.SpecialFunctions.Gaussian.GaussianIntegral
/-!
# Volume of balls
Let `E` be a finite dimensional normed `ℝ`-vector space equipped with a Haar measure `μ`. We
prove that
`μ (Metric.ball 0 1) = (∫ (x : E), Real.exp (- ‖x‖ ^ p) ∂μ) / Real.Gamma (finrank ℝ E / p + 1)`
for any real number `p` with `0 < p`, see `MeasureTheorymeasure_unitBall_eq_integral_div_gamma`. We
also prove the corresponding result to compute `μ {x : E | g x < 1}` where `g : E → ℝ` is a function
defining a norm on `E`, see `MeasureTheory.measure_lt_one_eq_integral_div_gamma`.
Using these formulas, we compute the volume of the unit balls in several cases.
* `MeasureTheory.volume_sum_rpow_lt` / `MeasureTheory.volume_sum_rpow_le`: volume of the open and
closed balls for the norm `Lp` over a real finite dimensional vector space with `1 ≤ p`. These
are computed as `volume {x : ι → ℝ | (∑ i, |x i| ^ p) ^ (1 / p) < r}` and
`volume {x : ι → ℝ | (∑ i, |x i| ^ p) ^ (1 / p) ≤ r}` since the spaces `PiLp` do not have a
`MeasureSpace` instance.
* `Complex.volume_sum_rpow_lt_one` / `Complex.volume_sum_rpow_lt`: same as above but for complex
finite dimensional vector space.
* `EuclideanSpace.volume_ball` / `EuclideanSpace.volume_closedBall` : volume of open and closed
balls in a finite dimensional Euclidean space.
* `InnerProductSpace.volume_ball` / `InnerProductSpace.volume_closedBall`: volume of open and closed
balls in a finite dimensional real inner product space.
* `Complex.volume_ball` / `Complex.volume_closedBall`: volume of open and closed balls in `ℂ`.
-/
section general_case
open MeasureTheory MeasureTheory.Measure Module ENNReal
theorem MeasureTheory.measure_unitBall_eq_integral_div_gamma {E : Type*} {p : ℝ}
[NormedAddCommGroup E] [NormedSpace ℝ E] [FiniteDimensional ℝ E] [MeasurableSpace E]
[BorelSpace E] (μ : Measure E) [IsAddHaarMeasure μ] (hp : 0 < p) :
μ (Metric.ball 0 1) =
.ofReal ((∫ (x : E), Real.exp (- ‖x‖ ^ p) ∂μ) / Real.Gamma (finrank ℝ E / p + 1)) := by
obtain hE | hE := subsingleton_or_nontrivial E
· rw [(Metric.nonempty_ball.mpr zero_lt_one).eq_zero, ← setIntegral_univ,
Set.univ_nonempty.eq_zero, integral_singleton, finrank_zero_of_subsingleton, Nat.cast_zero,
zero_div, zero_add, Real.Gamma_one, div_one, norm_zero, Real.zero_rpow hp.ne', neg_zero,
Real.exp_zero, smul_eq_mul, mul_one, measureReal_def, ofReal_toReal (measure_ne_top μ {0})]
· have : (0 : ℝ) < finrank ℝ E := Nat.cast_pos.mpr finrank_pos
have : ((∫ y in Set.Ioi (0 : ℝ), y ^ (finrank ℝ E - 1) • Real.exp (-y ^ p)) /
Real.Gamma ((finrank ℝ E) / p + 1)) * (finrank ℝ E) = 1 := by
simp_rw [← Real.rpow_natCast _ (finrank ℝ E - 1), smul_eq_mul, Nat.cast_sub finrank_pos,
Nat.cast_one]
rw [integral_rpow_mul_exp_neg_rpow hp (by linarith), sub_add_cancel,
Real.Gamma_add_one (ne_of_gt (by positivity))]
field_simp; ring
rw [integral_fun_norm_addHaar μ (fun x => Real.exp (- x ^ p)), nsmul_eq_mul, smul_eq_mul,
mul_div_assoc, mul_div_assoc, mul_comm, mul_assoc, this, mul_one, ofReal_measureReal _]
exact ne_of_lt measure_ball_lt_top
variable {E : Type*} [AddCommGroup E] [Module ℝ E] [FiniteDimensional ℝ E] [mE : MeasurableSpace E]
[tE : TopologicalSpace E] [IsTopologicalAddGroup E] [BorelSpace E] [T2Space E]
[ContinuousSMul ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {g : E → ℝ} (h1 : g 0 = 0)
(h2 : ∀ x, g (-x) = g x) (h3 : ∀ x y, g (x + y) ≤ g x + g y) (h4 : ∀ {x}, g x = 0 → x = 0)
(h5 : ∀ r x, g (r • x) ≤ |r| * (g x))
include h1 h2 h3 h4 h5
theorem MeasureTheory.measure_lt_one_eq_integral_div_gamma {p : ℝ} (hp : 0 < p) :
μ {x : E | g x < 1} =
.ofReal ((∫ (x : E), Real.exp (- (g x) ^ p) ∂μ) / Real.Gamma (finrank ℝ E / p + 1)) := by
-- We copy `E` to a new type `F` on which we will put the norm defined by `g`
letI F : Type _ := E
letI : NormedAddCommGroup F :=
{ norm := g
dist := fun x y => g (x - y)
dist_self := by simp only [_root_.sub_self, h1, forall_const]
dist_comm := fun _ _ => by rw [← h2, neg_sub]
dist_triangle := fun x y z => by convert h3 (x - y) (y - z) using 1; simp [F]
edist := fun x y => .ofReal (g (x - y))
edist_dist := fun _ _ => rfl
eq_of_dist_eq_zero := by convert fun _ _ h => eq_of_sub_eq_zero (h4 h) }
letI : NormedSpace ℝ F :=
{ norm_smul_le := fun _ _ ↦ h5 _ _ }
-- We put the new topology on F
letI : TopologicalSpace F := UniformSpace.toTopologicalSpace
letI : MeasurableSpace F := borel F
have : BorelSpace F := { measurable_eq := rfl }
-- The map between `E` and `F` as a continuous linear equivalence
let φ := @LinearEquiv.toContinuousLinearEquiv ℝ _ E _ _ tE _ _ F _ _ _ _ _ _ _ _ _
(LinearEquiv.refl ℝ E : E ≃ₗ[ℝ] F)
-- The measure `ν` is the measure on `F` defined by `μ`
-- Since we have two different topologies, it is necessary to specify the topology of E
let ν : Measure F := @Measure.map E F mE _ φ μ
have : IsAddHaarMeasure ν :=
@ContinuousLinearEquiv.isAddHaarMeasure_map E F ℝ ℝ _ _ _ _ _ _ tE _ _ _ _ _ _ _ mE _ _ _ φ μ _
convert (measure_unitBall_eq_integral_div_gamma ν hp) using 1
· rw [@Measure.map_apply E F mE _ μ φ _ _ measurableSet_ball]
· congr!
simp_rw [Metric.ball, dist_zero_right]
rfl
· refine @Continuous.measurable E F tE mE _ _ _ _ φ ?_
exact @ContinuousLinearEquiv.continuous ℝ ℝ _ _ _ _ _ _ E tE _ F _ _ _ _ φ
· -- The map between `E` and `F` as a measurable equivalence
let ψ := @Homeomorph.toMeasurableEquiv E F tE mE _ _ _ _
(@ContinuousLinearEquiv.toHomeomorph ℝ ℝ _ _ _ _ _ _ E tE _ F _ _ _ _ φ)
-- The map `ψ` is measure preserving by construction
have : @MeasurePreserving E F mE _ ψ μ ν :=
@Measurable.measurePreserving E F mE _ ψ (@MeasurableEquiv.measurable E F mE _ ψ) _
rw [← this.integral_comp']
rfl
theorem MeasureTheory.measure_le_eq_lt [Nontrivial E] (r : ℝ) :
μ {x : E | g x ≤ r} = μ {x : E | g x < r} := by
-- We copy `E` to a new type `F` on which we will put the norm defined by `g`
letI F : Type _ := E
letI : NormedAddCommGroup F :=
{ norm := g
dist := fun x y => g (x - y)
dist_self := by simp only [_root_.sub_self, h1, forall_const]
dist_comm := fun _ _ => by rw [← h2, neg_sub]
dist_triangle := fun x y z => by convert h3 (x - y) (y - z) using 1; simp [F]
edist := fun x y => .ofReal (g (x - y))
edist_dist := fun _ _ => rfl
eq_of_dist_eq_zero := by convert fun _ _ h => eq_of_sub_eq_zero (h4 h) }
letI : NormedSpace ℝ F :=
{ norm_smul_le := fun _ _ ↦ h5 _ _ }
-- We put the new topology on F
letI : TopologicalSpace F := UniformSpace.toTopologicalSpace
letI : MeasurableSpace F := borel F
have : BorelSpace F := { measurable_eq := rfl }
-- The map between `E` and `F` as a continuous linear equivalence
let φ := @LinearEquiv.toContinuousLinearEquiv ℝ _ E _ _ tE _ _ F _ _ _ _ _ _ _ _ _
(LinearEquiv.refl ℝ E : E ≃ₗ[ℝ] F)
-- The measure `ν` is the measure on `F` defined by `μ`
-- Since we have two different topologies, it is necessary to specify the topology of E
let ν : Measure F := @Measure.map E F mE _ φ μ
have : IsAddHaarMeasure ν :=
@ContinuousLinearEquiv.isAddHaarMeasure_map E F ℝ ℝ _ _ _ _ _ _ tE _ _ _ _ _ _ _ mE _ _ _ φ μ _
convert addHaar_closedBall_eq_addHaar_ball ν 0 r using 1
· rw [@Measure.map_apply E F mE _ μ φ _ _ measurableSet_closedBall]
· congr!
simp_rw [Metric.closedBall, dist_zero_right]
rfl
· refine @Continuous.measurable E F tE mE _ _ _ _ φ ?_
exact @ContinuousLinearEquiv.continuous ℝ ℝ _ _ _ _ _ _ E tE _ F _ _ _ _ φ
· rw [@Measure.map_apply E F mE _ μ φ _ _ measurableSet_ball]
· congr!
simp_rw [Metric.ball, dist_zero_right]
rfl
· refine @Continuous.measurable E F tE mE _ _ _ _ φ ?_
exact @ContinuousLinearEquiv.continuous ℝ ℝ _ _ _ _ _ _ E tE _ F _ _ _ _ φ
end general_case
section LpSpace
open Real Fintype ENNReal Module MeasureTheory MeasureTheory.Measure
variable (ι : Type*) [Fintype ι] {p : ℝ}
theorem MeasureTheory.volume_sum_rpow_lt_one (hp : 1 ≤ p) :
volume {x : ι → ℝ | ∑ i, |x i| ^ p < 1} =
.ofReal ((2 * Gamma (1 / p + 1)) ^ card ι / Gamma (card ι / p + 1)) := by
have h₁ : 0 < p := by linarith
have h₂ : ∀ x : ι → ℝ, 0 ≤ ∑ i, |x i| ^ p := by
refine fun _ => Finset.sum_nonneg' ?_
exact fun i => (fun _ => rpow_nonneg (abs_nonneg _) _) _
-- We collect facts about `Lp` norms that will be used in `measure_lt_one_eq_integral_div_gamma`
have eq_norm := fun x : ι → ℝ => (PiLp.norm_eq_sum (p := .ofReal p) (f := x)
((toReal_ofReal (le_of_lt h₁)).symm ▸ h₁))
simp_rw [toReal_ofReal (le_of_lt h₁), Real.norm_eq_abs] at eq_norm
have : Fact (1 ≤ ENNReal.ofReal p) := fact_iff.mpr (ofReal_one ▸ (ofReal_le_ofReal hp))
have nm_zero := norm_zero (E := PiLp (.ofReal p) (fun _ : ι => ℝ))
have eq_zero := fun x : ι → ℝ => norm_eq_zero (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) (a := x)
have nm_neg := fun x : ι → ℝ => norm_neg (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) x
have nm_add := fun x y : ι → ℝ => norm_add_le (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) x y
simp_rw [eq_norm] at eq_zero nm_zero nm_neg nm_add
have nm_smul := fun (r : ℝ) (x : ι → ℝ) =>
norm_smul_le (β := PiLp (.ofReal p) (fun _ : ι => ℝ)) r x
simp_rw [eq_norm, norm_eq_abs] at nm_smul
-- We use `measure_lt_one_eq_integral_div_gamma` with `g` equals to the norm `L_p`
convert (measure_lt_one_eq_integral_div_gamma (volume : Measure (ι → ℝ))
(g := fun x => (∑ i, |x i| ^ p) ^ (1 / p)) nm_zero nm_neg nm_add (eq_zero _).mp
(fun r x => nm_smul r x) (by linarith : 0 < p)) using 4
· rw [rpow_lt_one_iff' _ (one_div_pos.mpr h₁)]
exact Finset.sum_nonneg' (fun _ => rpow_nonneg (abs_nonneg _) _)
· simp_rw [← rpow_mul (h₂ _), div_mul_cancel₀ _ (ne_of_gt h₁), Real.rpow_one,
← Finset.sum_neg_distrib, exp_sum]
rw [integral_fintype_prod_eq_pow ι fun x : ℝ => exp (- |x| ^ p), integral_comp_abs
(f := fun x => exp (- x ^ p)), integral_exp_neg_rpow h₁]
· rw [finrank_fintype_fun_eq_card]
theorem MeasureTheory.volume_sum_rpow_lt [Nonempty ι] {p : ℝ} (hp : 1 ≤ p) (r : ℝ) :
volume {x : ι → ℝ | (∑ i, |x i| ^ p) ^ (1 / p) < r} = (.ofReal r) ^ card ι *
.ofReal ((2 * Gamma (1 / p + 1)) ^ card ι / Gamma (card ι / p + 1)) := by
have h₁ (x : ι → ℝ) : 0 ≤ ∑ i, |x i| ^ p := by positivity
have h₂ : ∀ x : ι → ℝ, 0 ≤ (∑ i, |x i| ^ p) ^ (1 / p) := fun x => rpow_nonneg (h₁ x) _
obtain hr | hr := le_or_lt r 0
· have : {x : ι → ℝ | (∑ i, |x i| ^ p) ^ (1 / p) < r} = ∅ := by
ext x
refine ⟨fun hx => ?_, fun hx => hx.elim⟩
exact not_le.mpr (lt_of_lt_of_le (Set.mem_setOf.mp hx) hr) (h₂ x)
rw [this, measure_empty, ← zero_eq_ofReal.mpr hr, zero_pow Fin.pos'.ne', zero_mul]
· rw [← volume_sum_rpow_lt_one _ hp, ← ofReal_pow (le_of_lt hr), ← finrank_pi ℝ]
convert addHaar_smul_of_nonneg volume (le_of_lt hr) {x : ι → ℝ | ∑ i, |x i| ^ p < 1} using 2
simp_rw [← Set.preimage_smul_inv₀ (ne_of_gt hr), Set.preimage_setOf_eq, Pi.smul_apply,
smul_eq_mul, abs_mul, mul_rpow (abs_nonneg _) (abs_nonneg _), abs_inv,
inv_rpow (abs_nonneg _), ← Finset.mul_sum, abs_eq_self.mpr (le_of_lt hr),
inv_mul_lt_iff₀ (rpow_pos_of_pos hr _), mul_one, ← rpow_lt_rpow_iff
(rpow_nonneg (h₁ _) _) (le_of_lt hr) (by linarith : 0 < p), ← rpow_mul
(h₁ _), div_mul_cancel₀ _ (ne_of_gt (by linarith) : p ≠ 0), Real.rpow_one]
| Mathlib/MeasureTheory/Measure/Lebesgue/VolumeOfBalls.lean | 220 | 238 | theorem MeasureTheory.volume_sum_rpow_le [Nonempty ι] {p : ℝ} (hp : 1 ≤ p) (r : ℝ) :
volume {x : ι → ℝ | (∑ i, |x i| ^ p) ^ (1 / p) ≤ r} = (.ofReal r) ^ card ι *
.ofReal ((2 * Gamma (1 / p + 1)) ^ card ι / Gamma (card ι / p + 1)) := by | have h₁ : 0 < p := by linarith
-- We collect facts about `Lp` norms that will be used in `measure_le_one_eq_lt_one`
have eq_norm := fun x : ι → ℝ => (PiLp.norm_eq_sum (p := .ofReal p) (f := x)
((toReal_ofReal (le_of_lt h₁)).symm ▸ h₁))
simp_rw [toReal_ofReal (le_of_lt h₁), Real.norm_eq_abs] at eq_norm
have : Fact (1 ≤ ENNReal.ofReal p) := fact_iff.mpr (ofReal_one ▸ (ofReal_le_ofReal hp))
have nm_zero := norm_zero (E := PiLp (.ofReal p) (fun _ : ι => ℝ))
have eq_zero := fun x : ι → ℝ => norm_eq_zero (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) (a := x)
have nm_neg := fun x : ι → ℝ => norm_neg (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) x
have nm_add := fun x y : ι → ℝ => norm_add_le (E := PiLp (.ofReal p) (fun _ : ι => ℝ)) x y
simp_rw [eq_norm] at eq_zero nm_zero nm_neg nm_add
have nm_smul := fun (r : ℝ) (x : ι → ℝ) =>
norm_smul_le (β := PiLp (.ofReal p) (fun _ : ι => ℝ)) r x
simp_rw [eq_norm, norm_eq_abs] at nm_smul
rw [measure_le_eq_lt _ nm_zero (fun x ↦ nm_neg x) (fun x y ↦ nm_add x y) (eq_zero _).mp
(fun r x => nm_smul r x), volume_sum_rpow_lt _ hp] |
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura, Jeremy Avigad, Minchao Wu, Mario Carneiro
-/
import Mathlib.Algebra.NeZero
import Mathlib.Data.Finset.Attach
import Mathlib.Data.Finset.Disjoint
import Mathlib.Data.Finset.Erase
import Mathlib.Data.Finset.Filter
import Mathlib.Data.Finset.Range
import Mathlib.Data.Finset.SDiff
/-! # Image and map operations on finite sets
This file provides the finite analog of `Set.image`, along with some other similar functions.
Note there are two ways to take the image over a finset; via `Finset.image` which applies the
function then removes duplicates (requiring `DecidableEq`), or via `Finset.map` which exploits
injectivity of the function to avoid needing to deduplicate. Choosing between these is similar to
choosing between `insert` and `Finset.cons`, or between `Finset.union` and `Finset.disjUnion`.
## Main definitions
* `Finset.image`: Given a function `f : α → β`, `s.image f` is the image finset in `β`.
* `Finset.map`: Given an embedding `f : α ↪ β`, `s.map f` is the image finset in `β`.
* `Finset.filterMap` Given a function `f : α → Option β`, `s.filterMap f` is the
image finset in `β`, filtering out `none`s.
* `Finset.subtype`: `s.subtype p` is the finset of `Subtype p` whose elements belong to `s`.
* `Finset.fin`:`s.fin n` is the finset of all elements of `s` less than `n`.
-/
assert_not_exists Monoid OrderedCommMonoid
variable {α β γ : Type*}
open Multiset
open Function
namespace Finset
/-! ### map -/
section Map
open Function
/-- When `f` is an embedding of `α` in `β` and `s` is a finset in `α`, then `s.map f` is the image
finset in `β`. The embedding condition guarantees that there are no duplicates in the image. -/
def map (f : α ↪ β) (s : Finset α) : Finset β :=
⟨s.1.map f, s.2.map f.2⟩
@[simp]
theorem map_val (f : α ↪ β) (s : Finset α) : (map f s).1 = s.1.map f :=
rfl
@[simp]
theorem map_empty (f : α ↪ β) : (∅ : Finset α).map f = ∅ :=
rfl
variable {f : α ↪ β} {s : Finset α}
@[simp]
theorem mem_map {b : β} : b ∈ s.map f ↔ ∃ a ∈ s, f a = b :=
Multiset.mem_map
-- Higher priority to apply before `mem_map`.
@[simp 1100]
theorem mem_map_equiv {f : α ≃ β} {b : β} : b ∈ s.map f.toEmbedding ↔ f.symm b ∈ s := by
rw [mem_map]
exact
⟨by
rintro ⟨a, H, rfl⟩
simpa, fun h => ⟨_, h, by simp⟩⟩
@[simp 1100]
theorem mem_map' (f : α ↪ β) {a} {s : Finset α} : f a ∈ s.map f ↔ a ∈ s :=
mem_map_of_injective f.2
theorem mem_map_of_mem (f : α ↪ β) {a} {s : Finset α} : a ∈ s → f a ∈ s.map f :=
(mem_map' _).2
theorem forall_mem_map {f : α ↪ β} {s : Finset α} {p : ∀ a, a ∈ s.map f → Prop} :
(∀ y (H : y ∈ s.map f), p y H) ↔ ∀ x (H : x ∈ s), p (f x) (mem_map_of_mem _ H) :=
⟨fun h y hy => h (f y) (mem_map_of_mem _ hy),
fun h x hx => by
obtain ⟨y, hy, rfl⟩ := mem_map.1 hx
exact h _ hy⟩
theorem apply_coe_mem_map (f : α ↪ β) (s : Finset α) (x : s) : f x ∈ s.map f :=
mem_map_of_mem f x.prop
@[simp, norm_cast]
theorem coe_map (f : α ↪ β) (s : Finset α) : (s.map f : Set β) = f '' s :=
Set.ext (by simp only [mem_coe, mem_map, Set.mem_image, implies_true])
theorem coe_map_subset_range (f : α ↪ β) (s : Finset α) : (s.map f : Set β) ⊆ Set.range f :=
calc
↑(s.map f) = f '' s := coe_map f s
_ ⊆ Set.range f := Set.image_subset_range f ↑s
/-- If the only elements outside `s` are those left fixed by `σ`, then mapping by `σ` has no effect.
-/
theorem map_perm {σ : Equiv.Perm α} (hs : { a | σ a ≠ a } ⊆ s) : s.map (σ : α ↪ α) = s :=
coe_injective <| (coe_map _ _).trans <| Set.image_perm hs
theorem map_toFinset [DecidableEq α] [DecidableEq β] {s : Multiset α} :
s.toFinset.map f = (s.map f).toFinset :=
ext fun _ => by simp only [mem_map, Multiset.mem_map, exists_prop, Multiset.mem_toFinset]
@[simp]
theorem map_refl : s.map (Embedding.refl _) = s :=
ext fun _ => by simpa only [mem_map, exists_prop] using exists_eq_right
@[simp]
theorem map_cast_heq {α β} (h : α = β) (s : Finset α) :
HEq (s.map (Equiv.cast h).toEmbedding) s := by
subst h
simp
theorem map_map (f : α ↪ β) (g : β ↪ γ) (s : Finset α) : (s.map f).map g = s.map (f.trans g) :=
eq_of_veq <| by simp only [map_val, Multiset.map_map]; rfl
theorem map_comm {β'} {f : β ↪ γ} {g : α ↪ β} {f' : α ↪ β'} {g' : β' ↪ γ}
(h_comm : ∀ a, f (g a) = g' (f' a)) : (s.map g).map f = (s.map f').map g' := by
simp_rw [map_map, Embedding.trans, Function.comp_def, h_comm]
theorem _root_.Function.Semiconj.finset_map {f : α ↪ β} {ga : α ↪ α} {gb : β ↪ β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (map f) (map ga) (map gb) := fun _ =>
map_comm h
theorem _root_.Function.Commute.finset_map {f g : α ↪ α} (h : Function.Commute f g) :
Function.Commute (map f) (map g) :=
Function.Semiconj.finset_map h
@[simp]
theorem map_subset_map {s₁ s₂ : Finset α} : s₁.map f ⊆ s₂.map f ↔ s₁ ⊆ s₂ :=
⟨fun h _ xs => (mem_map' _).1 <| h <| (mem_map' f).2 xs,
fun h => by simp [subset_def, Multiset.map_subset_map h]⟩
@[gcongr] alias ⟨_, _root_.GCongr.finsetMap_subset⟩ := map_subset_map
/-- The `Finset` version of `Equiv.subset_symm_image`. -/
theorem subset_map_symm {t : Finset β} {f : α ≃ β} : s ⊆ t.map f.symm ↔ s.map f ⊆ t := by
constructor <;> intro h x hx
· simp only [mem_map_equiv, Equiv.symm_symm] at hx
simpa using h hx
· simp only [mem_map_equiv]
exact h (by simp [hx])
/-- The `Finset` version of `Equiv.symm_image_subset`. -/
theorem map_symm_subset {t : Finset β} {f : α ≃ β} : t.map f.symm ⊆ s ↔ t ⊆ s.map f := by
simp only [← subset_map_symm, Equiv.symm_symm]
/-- Associate to an embedding `f` from `α` to `β` the order embedding that maps a finset to its
image under `f`. -/
def mapEmbedding (f : α ↪ β) : Finset α ↪o Finset β :=
OrderEmbedding.ofMapLEIff (map f) fun _ _ => map_subset_map
@[simp]
theorem map_inj {s₁ s₂ : Finset α} : s₁.map f = s₂.map f ↔ s₁ = s₂ :=
(mapEmbedding f).injective.eq_iff
theorem map_injective (f : α ↪ β) : Injective (map f) :=
(mapEmbedding f).injective
@[simp]
theorem map_ssubset_map {s t : Finset α} : s.map f ⊂ t.map f ↔ s ⊂ t := (mapEmbedding f).lt_iff_lt
@[gcongr] alias ⟨_, _root_.GCongr.finsetMap_ssubset⟩ := map_ssubset_map
@[simp]
theorem mapEmbedding_apply : mapEmbedding f s = map f s :=
rfl
theorem filter_map {p : β → Prop} [DecidablePred p] :
(s.map f).filter p = (s.filter (p ∘ f)).map f :=
eq_of_veq (Multiset.filter_map _ _ _)
lemma map_filter' (p : α → Prop) [DecidablePred p] (f : α ↪ β) (s : Finset α)
[DecidablePred (∃ a, p a ∧ f a = ·)] :
(s.filter p).map f = (s.map f).filter fun b => ∃ a, p a ∧ f a = b := by
simp [Function.comp_def, filter_map, f.injective.eq_iff]
lemma filter_attach' [DecidableEq α] (s : Finset α) (p : s → Prop) [DecidablePred p] :
s.attach.filter p =
(s.filter fun x => ∃ h, p ⟨x, h⟩).attach.map
⟨Subtype.map id <| filter_subset _ _, Subtype.map_injective _ injective_id⟩ :=
eq_of_veq <| Multiset.filter_attach' _ _
lemma filter_attach (p : α → Prop) [DecidablePred p] (s : Finset α) :
s.attach.filter (fun a : s ↦ p a) =
(s.filter p).attach.map ((Embedding.refl _).subtypeMap mem_of_mem_filter) :=
eq_of_veq <| Multiset.filter_attach _ _
theorem map_filter {f : α ≃ β} {p : α → Prop} [DecidablePred p] :
(s.filter p).map f.toEmbedding = (s.map f.toEmbedding).filter (p ∘ f.symm) := by
simp only [filter_map, Function.comp_def, Equiv.toEmbedding_apply, Equiv.symm_apply_apply]
@[simp]
theorem disjoint_map {s t : Finset α} (f : α ↪ β) :
Disjoint (s.map f) (t.map f) ↔ Disjoint s t :=
mod_cast Set.disjoint_image_iff f.injective (s := s) (t := t)
theorem map_disjUnion {f : α ↪ β} (s₁ s₂ : Finset α) (h) (h' := (disjoint_map _).mpr h) :
(s₁.disjUnion s₂ h).map f = (s₁.map f).disjUnion (s₂.map f) h' :=
eq_of_veq <| Multiset.map_add _ _ _
/-- A version of `Finset.map_disjUnion` for writing in the other direction. -/
theorem map_disjUnion' {f : α ↪ β} (s₁ s₂ : Finset α) (h') (h := (disjoint_map _).mp h') :
(s₁.disjUnion s₂ h).map f = (s₁.map f).disjUnion (s₂.map f) h' :=
map_disjUnion _ _ _
theorem map_union [DecidableEq α] [DecidableEq β] {f : α ↪ β} (s₁ s₂ : Finset α) :
(s₁ ∪ s₂).map f = s₁.map f ∪ s₂.map f :=
mod_cast Set.image_union f s₁ s₂
theorem map_inter [DecidableEq α] [DecidableEq β] {f : α ↪ β} (s₁ s₂ : Finset α) :
(s₁ ∩ s₂).map f = s₁.map f ∩ s₂.map f :=
mod_cast Set.image_inter f.injective (s := s₁) (t := s₂)
@[simp]
theorem map_singleton (f : α ↪ β) (a : α) : map f {a} = {f a} :=
coe_injective <| by simp only [coe_map, coe_singleton, Set.image_singleton]
@[simp]
theorem map_insert [DecidableEq α] [DecidableEq β] (f : α ↪ β) (a : α) (s : Finset α) :
(insert a s).map f = insert (f a) (s.map f) := by
simp only [insert_eq, map_union, map_singleton]
@[simp]
theorem map_cons (f : α ↪ β) (a : α) (s : Finset α) (ha : a ∉ s) :
(cons a s ha).map f = cons (f a) (s.map f) (by simpa using ha) :=
eq_of_veq <| Multiset.map_cons f a s.val
@[simp]
theorem map_eq_empty : s.map f = ∅ ↔ s = ∅ := (map_injective f).eq_iff' (map_empty f)
@[simp]
theorem map_nonempty : (s.map f).Nonempty ↔ s.Nonempty :=
mod_cast Set.image_nonempty (f := f) (s := s)
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected alias ⟨_, Nonempty.map⟩ := map_nonempty
@[simp]
theorem map_nontrivial : (s.map f).Nontrivial ↔ s.Nontrivial :=
mod_cast Set.image_nontrivial f.injective (s := s)
theorem attach_map_val {s : Finset α} : s.attach.map (Embedding.subtype _) = s :=
eq_of_veq <| by rw [map_val, attach_val]; exact Multiset.attach_map_val _
end Map
theorem range_add_one' (n : ℕ) :
range (n + 1) = insert 0 ((range n).map ⟨fun i => i + 1, fun i j => by simp⟩) := by
ext (⟨⟩ | ⟨n⟩) <;> simp [Nat.zero_lt_succ n]
/-! ### image -/
section Image
variable [DecidableEq β]
/-- `image f s` is the forward image of `s` under `f`. -/
def image (f : α → β) (s : Finset α) : Finset β :=
(s.1.map f).toFinset
@[simp]
theorem image_val (f : α → β) (s : Finset α) : (image f s).1 = (s.1.map f).dedup :=
rfl
@[simp]
theorem image_empty (f : α → β) : (∅ : Finset α).image f = ∅ :=
rfl
variable {f g : α → β} {s : Finset α} {t : Finset β} {a : α} {b c : β}
@[simp]
theorem mem_image : b ∈ s.image f ↔ ∃ a ∈ s, f a = b := by
simp only [mem_def, image_val, mem_dedup, Multiset.mem_map, exists_prop]
theorem mem_image_of_mem (f : α → β) {a} (h : a ∈ s) : f a ∈ s.image f :=
mem_image.2 ⟨_, h, rfl⟩
lemma forall_mem_image {p : β → Prop} : (∀ y ∈ s.image f, p y) ↔ ∀ ⦃x⦄, x ∈ s → p (f x) := by simp
lemma exists_mem_image {p : β → Prop} : (∃ y ∈ s.image f, p y) ↔ ∃ x ∈ s, p (f x) := by simp
@[deprecated (since := "2024-11-23")] alias forall_image := forall_mem_image
theorem map_eq_image (f : α ↪ β) (s : Finset α) : s.map f = s.image f :=
eq_of_veq (s.map f).2.dedup.symm
-- Not `@[simp]` since `mem_image` already gets most of the way there.
theorem mem_image_const : c ∈ s.image (const α b) ↔ s.Nonempty ∧ b = c := by
rw [mem_image]
simp only [exists_prop, const_apply, exists_and_right]
rfl
theorem mem_image_const_self : b ∈ s.image (const α b) ↔ s.Nonempty :=
mem_image_const.trans <| and_iff_left rfl
instance canLift (c) (p) [CanLift β α c p] :
CanLift (Finset β) (Finset α) (image c) fun s => ∀ x ∈ s, p x where
prf := by
rintro ⟨⟨l⟩, hd : l.Nodup⟩ hl
lift l to List α using hl
exact ⟨⟨l, hd.of_map _⟩, ext fun a => by simp⟩
theorem image_congr (h : (s : Set α).EqOn f g) : Finset.image f s = Finset.image g s := by
ext
simp_rw [mem_image, ← bex_def]
exact exists₂_congr fun x hx => by rw [h hx]
theorem _root_.Function.Injective.mem_finset_image (hf : Injective f) :
f a ∈ s.image f ↔ a ∈ s := by
refine ⟨fun h => ?_, Finset.mem_image_of_mem f⟩
obtain ⟨y, hy, heq⟩ := mem_image.1 h
exact hf heq ▸ hy
@[simp, norm_cast]
theorem coe_image : ↑(s.image f) = f '' ↑s :=
Set.ext <| by simp only [mem_coe, mem_image, Set.mem_image, implies_true]
@[simp]
lemma image_nonempty : (s.image f).Nonempty ↔ s.Nonempty :=
mod_cast Set.image_nonempty (f := f) (s := (s : Set α))
@[aesop safe apply (rule_sets := [finsetNonempty])]
protected theorem Nonempty.image (h : s.Nonempty) (f : α → β) : (s.image f).Nonempty :=
image_nonempty.2 h
alias ⟨Nonempty.of_image, _⟩ := image_nonempty
theorem image_toFinset [DecidableEq α] {s : Multiset α} :
s.toFinset.image f = (s.map f).toFinset :=
ext fun _ => by simp only [mem_image, Multiset.mem_toFinset, exists_prop, Multiset.mem_map]
theorem image_val_of_injOn (H : Set.InjOn f s) : (image f s).1 = s.1.map f :=
(s.2.map_on H).dedup
@[simp]
theorem image_id [DecidableEq α] : s.image id = s :=
ext fun _ => by simp only [mem_image, exists_prop, id, exists_eq_right]
@[simp]
theorem image_id' [DecidableEq α] : (s.image fun x => x) = s :=
image_id
theorem image_image [DecidableEq γ] {g : β → γ} : (s.image f).image g = s.image (g ∘ f) :=
eq_of_veq <| by simp only [image_val, dedup_map_dedup_eq, Multiset.map_map]
theorem image_comm {β'} [DecidableEq β'] [DecidableEq γ] {f : β → γ} {g : α → β} {f' : α → β'}
{g' : β' → γ} (h_comm : ∀ a, f (g a) = g' (f' a)) :
(s.image g).image f = (s.image f').image g' := by simp_rw [image_image, comp_def, h_comm]
theorem _root_.Function.Semiconj.finset_image [DecidableEq α] {f : α → β} {ga : α → α} {gb : β → β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (image f) (image ga) (image gb) := fun _ =>
image_comm h
theorem _root_.Function.Commute.finset_image [DecidableEq α] {f g : α → α}
(h : Function.Commute f g) : Function.Commute (image f) (image g) :=
Function.Semiconj.finset_image h
theorem image_subset_image {s₁ s₂ : Finset α} (h : s₁ ⊆ s₂) : s₁.image f ⊆ s₂.image f := by
simp only [subset_def, image_val, subset_dedup', dedup_subset', Multiset.map_subset_map h]
theorem image_subset_iff : s.image f ⊆ t ↔ ∀ x ∈ s, f x ∈ t :=
calc
s.image f ⊆ t ↔ f '' ↑s ⊆ ↑t := by norm_cast
_ ↔ _ := Set.image_subset_iff
theorem image_mono (f : α → β) : Monotone (Finset.image f) := fun _ _ => image_subset_image
lemma image_injective (hf : Injective f) : Injective (image f) := by
simpa only [funext (map_eq_image _)] using map_injective ⟨f, hf⟩
lemma image_inj {t : Finset α} (hf : Injective f) : s.image f = t.image f ↔ s = t :=
(image_injective hf).eq_iff
theorem image_subset_image_iff {t : Finset α} (hf : Injective f) :
s.image f ⊆ t.image f ↔ s ⊆ t :=
mod_cast Set.image_subset_image_iff hf (s := s) (t := t)
lemma image_ssubset_image {t : Finset α} (hf : Injective f) : s.image f ⊂ t.image f ↔ s ⊂ t := by
simp_rw [← lt_iff_ssubset]
exact lt_iff_lt_of_le_iff_le' (image_subset_image_iff hf) (image_subset_image_iff hf)
theorem coe_image_subset_range : ↑(s.image f) ⊆ Set.range f :=
calc
↑(s.image f) = f '' ↑s := coe_image
_ ⊆ Set.range f := Set.image_subset_range f ↑s
theorem filter_image {p : β → Prop} [DecidablePred p] :
(s.image f).filter p = (s.filter fun a ↦ p (f a)).image f :=
ext fun b => by
simp only [mem_filter, mem_image, exists_prop]
exact
⟨by rintro ⟨⟨x, h1, rfl⟩, h2⟩; exact ⟨x, ⟨h1, h2⟩, rfl⟩,
by rintro ⟨x, ⟨h1, h2⟩, rfl⟩; exact ⟨⟨x, h1, rfl⟩, h2⟩⟩
| Mathlib/Data/Finset/Image.lean | 405 | 411 | theorem fiber_nonempty_iff_mem_image {y : β} : (s.filter (f · = y)).Nonempty ↔ y ∈ s.image f := by | simp [Finset.Nonempty]
theorem image_union [DecidableEq α] {f : α → β} (s₁ s₂ : Finset α) :
(s₁ ∪ s₂).image f = s₁.image f ∪ s₂.image f :=
mod_cast Set.image_union f s₁ s₂ |
/-
Copyright (c) 2014 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Logic.Pairwise
import Mathlib.Data.Set.BooleanAlgebra
/-!
# The set lattice
This file is a collection of results on the complete atomic boolean algebra structure of `Set α`.
Notation for the complete lattice operations can be found in `Mathlib.Order.SetNotation`.
## Main declarations
* `Set.sInter_eq_biInter`, `Set.sUnion_eq_biInter`: Shows that `⋂₀ s = ⋂ x ∈ s, x` and
`⋃₀ s = ⋃ x ∈ s, x`.
* `Set.completeAtomicBooleanAlgebra`: `Set α` is a `CompleteAtomicBooleanAlgebra` with `≤ = ⊆`,
`< = ⊂`, `⊓ = ∩`, `⊔ = ∪`, `⨅ = ⋂`, `⨆ = ⋃` and `\` as the set difference.
See `Set.instBooleanAlgebra`.
* `Set.unionEqSigmaOfDisjoint`: Equivalence between `⋃ i, t i` and `Σ i, t i`, where `t` is an
indexed family of disjoint sets.
## Naming convention
In lemma names,
* `⋃ i, s i` is called `iUnion`
* `⋂ i, s i` is called `iInter`
* `⋃ i j, s i j` is called `iUnion₂`. This is an `iUnion` inside an `iUnion`.
* `⋂ i j, s i j` is called `iInter₂`. This is an `iInter` inside an `iInter`.
* `⋃ i ∈ s, t i` is called `biUnion` for "bounded `iUnion`". This is the special case of `iUnion₂`
where `j : i ∈ s`.
* `⋂ i ∈ s, t i` is called `biInter` for "bounded `iInter`". This is the special case of `iInter₂`
where `j : i ∈ s`.
## Notation
* `⋃`: `Set.iUnion`
* `⋂`: `Set.iInter`
* `⋃₀`: `Set.sUnion`
* `⋂₀`: `Set.sInter`
-/
open Function Set
universe u
variable {α β γ δ : Type*} {ι ι' ι₂ : Sort*} {κ κ₁ κ₂ : ι → Sort*} {κ' : ι' → Sort*}
namespace Set
/-! ### Complete lattice and complete Boolean algebra instances -/
theorem mem_iUnion₂ {x : γ} {s : ∀ i, κ i → Set γ} : (x ∈ ⋃ (i) (j), s i j) ↔ ∃ i j, x ∈ s i j := by
simp_rw [mem_iUnion]
theorem mem_iInter₂ {x : γ} {s : ∀ i, κ i → Set γ} : (x ∈ ⋂ (i) (j), s i j) ↔ ∀ i j, x ∈ s i j := by
simp_rw [mem_iInter]
theorem mem_iUnion_of_mem {s : ι → Set α} {a : α} (i : ι) (ha : a ∈ s i) : a ∈ ⋃ i, s i :=
mem_iUnion.2 ⟨i, ha⟩
theorem mem_iUnion₂_of_mem {s : ∀ i, κ i → Set α} {a : α} {i : ι} (j : κ i) (ha : a ∈ s i j) :
a ∈ ⋃ (i) (j), s i j :=
mem_iUnion₂.2 ⟨i, j, ha⟩
theorem mem_iInter_of_mem {s : ι → Set α} {a : α} (h : ∀ i, a ∈ s i) : a ∈ ⋂ i, s i :=
mem_iInter.2 h
theorem mem_iInter₂_of_mem {s : ∀ i, κ i → Set α} {a : α} (h : ∀ i j, a ∈ s i j) :
a ∈ ⋂ (i) (j), s i j :=
mem_iInter₂.2 h
/-! ### Union and intersection over an indexed family of sets -/
@[congr]
theorem iUnion_congr_Prop {p q : Prop} {f₁ : p → Set α} {f₂ : q → Set α} (pq : p ↔ q)
(f : ∀ x, f₁ (pq.mpr x) = f₂ x) : iUnion f₁ = iUnion f₂ :=
iSup_congr_Prop pq f
@[congr]
theorem iInter_congr_Prop {p q : Prop} {f₁ : p → Set α} {f₂ : q → Set α} (pq : p ↔ q)
(f : ∀ x, f₁ (pq.mpr x) = f₂ x) : iInter f₁ = iInter f₂ :=
iInf_congr_Prop pq f
theorem iUnion_plift_up (f : PLift ι → Set α) : ⋃ i, f (PLift.up i) = ⋃ i, f i :=
iSup_plift_up _
theorem iUnion_plift_down (f : ι → Set α) : ⋃ i, f (PLift.down i) = ⋃ i, f i :=
iSup_plift_down _
theorem iInter_plift_up (f : PLift ι → Set α) : ⋂ i, f (PLift.up i) = ⋂ i, f i :=
iInf_plift_up _
theorem iInter_plift_down (f : ι → Set α) : ⋂ i, f (PLift.down i) = ⋂ i, f i :=
iInf_plift_down _
theorem iUnion_eq_if {p : Prop} [Decidable p] (s : Set α) : ⋃ _ : p, s = if p then s else ∅ :=
iSup_eq_if _
theorem iUnion_eq_dif {p : Prop} [Decidable p] (s : p → Set α) :
⋃ h : p, s h = if h : p then s h else ∅ :=
iSup_eq_dif _
theorem iInter_eq_if {p : Prop} [Decidable p] (s : Set α) : ⋂ _ : p, s = if p then s else univ :=
iInf_eq_if _
theorem iInf_eq_dif {p : Prop} [Decidable p] (s : p → Set α) :
⋂ h : p, s h = if h : p then s h else univ :=
_root_.iInf_eq_dif _
theorem exists_set_mem_of_union_eq_top {ι : Type*} (t : Set ι) (s : ι → Set β)
(w : ⋃ i ∈ t, s i = ⊤) (x : β) : ∃ i ∈ t, x ∈ s i := by
have p : x ∈ ⊤ := Set.mem_univ x
rw [← w, Set.mem_iUnion] at p
simpa using p
theorem nonempty_of_union_eq_top_of_nonempty {ι : Type*} (t : Set ι) (s : ι → Set α)
(H : Nonempty α) (w : ⋃ i ∈ t, s i = ⊤) : t.Nonempty := by
obtain ⟨x, m, -⟩ := exists_set_mem_of_union_eq_top t s w H.some
exact ⟨x, m⟩
theorem nonempty_of_nonempty_iUnion
{s : ι → Set α} (h_Union : (⋃ i, s i).Nonempty) : Nonempty ι := by
obtain ⟨x, hx⟩ := h_Union
exact ⟨Classical.choose <| mem_iUnion.mp hx⟩
theorem nonempty_of_nonempty_iUnion_eq_univ
{s : ι → Set α} [Nonempty α] (h_Union : ⋃ i, s i = univ) : Nonempty ι :=
nonempty_of_nonempty_iUnion (s := s) (by simpa only [h_Union] using univ_nonempty)
theorem setOf_exists (p : ι → β → Prop) : { x | ∃ i, p i x } = ⋃ i, { x | p i x } :=
ext fun _ => mem_iUnion.symm
theorem setOf_forall (p : ι → β → Prop) : { x | ∀ i, p i x } = ⋂ i, { x | p i x } :=
ext fun _ => mem_iInter.symm
theorem iUnion_subset {s : ι → Set α} {t : Set α} (h : ∀ i, s i ⊆ t) : ⋃ i, s i ⊆ t :=
iSup_le h
theorem iUnion₂_subset {s : ∀ i, κ i → Set α} {t : Set α} (h : ∀ i j, s i j ⊆ t) :
⋃ (i) (j), s i j ⊆ t :=
iUnion_subset fun x => iUnion_subset (h x)
theorem subset_iInter {t : Set β} {s : ι → Set β} (h : ∀ i, t ⊆ s i) : t ⊆ ⋂ i, s i :=
le_iInf h
theorem subset_iInter₂ {s : Set α} {t : ∀ i, κ i → Set α} (h : ∀ i j, s ⊆ t i j) :
s ⊆ ⋂ (i) (j), t i j :=
subset_iInter fun x => subset_iInter <| h x
@[simp]
theorem iUnion_subset_iff {s : ι → Set α} {t : Set α} : ⋃ i, s i ⊆ t ↔ ∀ i, s i ⊆ t :=
⟨fun h _ => Subset.trans (le_iSup s _) h, iUnion_subset⟩
theorem iUnion₂_subset_iff {s : ∀ i, κ i → Set α} {t : Set α} :
⋃ (i) (j), s i j ⊆ t ↔ ∀ i j, s i j ⊆ t := by simp_rw [iUnion_subset_iff]
@[simp]
theorem subset_iInter_iff {s : Set α} {t : ι → Set α} : (s ⊆ ⋂ i, t i) ↔ ∀ i, s ⊆ t i :=
le_iInf_iff
theorem subset_iInter₂_iff {s : Set α} {t : ∀ i, κ i → Set α} :
(s ⊆ ⋂ (i) (j), t i j) ↔ ∀ i j, s ⊆ t i j := by simp_rw [subset_iInter_iff]
theorem subset_iUnion : ∀ (s : ι → Set β) (i : ι), s i ⊆ ⋃ i, s i :=
le_iSup
theorem iInter_subset : ∀ (s : ι → Set β) (i : ι), ⋂ i, s i ⊆ s i :=
iInf_le
lemma iInter_subset_iUnion [Nonempty ι] {s : ι → Set α} : ⋂ i, s i ⊆ ⋃ i, s i := iInf_le_iSup
theorem subset_iUnion₂ {s : ∀ i, κ i → Set α} (i : ι) (j : κ i) : s i j ⊆ ⋃ (i') (j'), s i' j' :=
le_iSup₂ i j
theorem iInter₂_subset {s : ∀ i, κ i → Set α} (i : ι) (j : κ i) : ⋂ (i) (j), s i j ⊆ s i j :=
iInf₂_le i j
/-- This rather trivial consequence of `subset_iUnion`is convenient with `apply`, and has `i`
explicit for this purpose. -/
theorem subset_iUnion_of_subset {s : Set α} {t : ι → Set α} (i : ι) (h : s ⊆ t i) : s ⊆ ⋃ i, t i :=
le_iSup_of_le i h
/-- This rather trivial consequence of `iInter_subset`is convenient with `apply`, and has `i`
explicit for this purpose. -/
theorem iInter_subset_of_subset {s : ι → Set α} {t : Set α} (i : ι) (h : s i ⊆ t) :
⋂ i, s i ⊆ t :=
iInf_le_of_le i h
/-- This rather trivial consequence of `subset_iUnion₂` is convenient with `apply`, and has `i` and
`j` explicit for this purpose. -/
theorem subset_iUnion₂_of_subset {s : Set α} {t : ∀ i, κ i → Set α} (i : ι) (j : κ i)
(h : s ⊆ t i j) : s ⊆ ⋃ (i) (j), t i j :=
le_iSup₂_of_le i j h
/-- This rather trivial consequence of `iInter₂_subset` is convenient with `apply`, and has `i` and
`j` explicit for this purpose. -/
theorem iInter₂_subset_of_subset {s : ∀ i, κ i → Set α} {t : Set α} (i : ι) (j : κ i)
(h : s i j ⊆ t) : ⋂ (i) (j), s i j ⊆ t :=
iInf₂_le_of_le i j h
theorem iUnion_mono {s t : ι → Set α} (h : ∀ i, s i ⊆ t i) : ⋃ i, s i ⊆ ⋃ i, t i :=
iSup_mono h
@[gcongr]
theorem iUnion_mono'' {s t : ι → Set α} (h : ∀ i, s i ⊆ t i) : iUnion s ⊆ iUnion t :=
iSup_mono h
theorem iUnion₂_mono {s t : ∀ i, κ i → Set α} (h : ∀ i j, s i j ⊆ t i j) :
⋃ (i) (j), s i j ⊆ ⋃ (i) (j), t i j :=
iSup₂_mono h
theorem iInter_mono {s t : ι → Set α} (h : ∀ i, s i ⊆ t i) : ⋂ i, s i ⊆ ⋂ i, t i :=
iInf_mono h
@[gcongr]
theorem iInter_mono'' {s t : ι → Set α} (h : ∀ i, s i ⊆ t i) : iInter s ⊆ iInter t :=
iInf_mono h
theorem iInter₂_mono {s t : ∀ i, κ i → Set α} (h : ∀ i j, s i j ⊆ t i j) :
⋂ (i) (j), s i j ⊆ ⋂ (i) (j), t i j :=
iInf₂_mono h
theorem iUnion_mono' {s : ι → Set α} {t : ι₂ → Set α} (h : ∀ i, ∃ j, s i ⊆ t j) :
⋃ i, s i ⊆ ⋃ i, t i :=
iSup_mono' h
theorem iUnion₂_mono' {s : ∀ i, κ i → Set α} {t : ∀ i', κ' i' → Set α}
(h : ∀ i j, ∃ i' j', s i j ⊆ t i' j') : ⋃ (i) (j), s i j ⊆ ⋃ (i') (j'), t i' j' :=
iSup₂_mono' h
theorem iInter_mono' {s : ι → Set α} {t : ι' → Set α} (h : ∀ j, ∃ i, s i ⊆ t j) :
⋂ i, s i ⊆ ⋂ j, t j :=
Set.subset_iInter fun j =>
let ⟨i, hi⟩ := h j
iInter_subset_of_subset i hi
theorem iInter₂_mono' {s : ∀ i, κ i → Set α} {t : ∀ i', κ' i' → Set α}
(h : ∀ i' j', ∃ i j, s i j ⊆ t i' j') : ⋂ (i) (j), s i j ⊆ ⋂ (i') (j'), t i' j' :=
subset_iInter₂_iff.2 fun i' j' =>
let ⟨_, _, hst⟩ := h i' j'
(iInter₂_subset _ _).trans hst
theorem iUnion₂_subset_iUnion (κ : ι → Sort*) (s : ι → Set α) :
⋃ (i) (_ : κ i), s i ⊆ ⋃ i, s i :=
iUnion_mono fun _ => iUnion_subset fun _ => Subset.rfl
theorem iInter_subset_iInter₂ (κ : ι → Sort*) (s : ι → Set α) :
⋂ i, s i ⊆ ⋂ (i) (_ : κ i), s i :=
iInter_mono fun _ => subset_iInter fun _ => Subset.rfl
theorem iUnion_setOf (P : ι → α → Prop) : ⋃ i, { x : α | P i x } = { x : α | ∃ i, P i x } := by
ext
exact mem_iUnion
theorem iInter_setOf (P : ι → α → Prop) : ⋂ i, { x : α | P i x } = { x : α | ∀ i, P i x } := by
ext
exact mem_iInter
theorem iUnion_congr_of_surjective {f : ι → Set α} {g : ι₂ → Set α} (h : ι → ι₂) (h1 : Surjective h)
(h2 : ∀ x, g (h x) = f x) : ⋃ x, f x = ⋃ y, g y :=
h1.iSup_congr h h2
theorem iInter_congr_of_surjective {f : ι → Set α} {g : ι₂ → Set α} (h : ι → ι₂) (h1 : Surjective h)
(h2 : ∀ x, g (h x) = f x) : ⋂ x, f x = ⋂ y, g y :=
h1.iInf_congr h h2
lemma iUnion_congr {s t : ι → Set α} (h : ∀ i, s i = t i) : ⋃ i, s i = ⋃ i, t i := iSup_congr h
lemma iInter_congr {s t : ι → Set α} (h : ∀ i, s i = t i) : ⋂ i, s i = ⋂ i, t i := iInf_congr h
lemma iUnion₂_congr {s t : ∀ i, κ i → Set α} (h : ∀ i j, s i j = t i j) :
⋃ (i) (j), s i j = ⋃ (i) (j), t i j :=
iUnion_congr fun i => iUnion_congr <| h i
lemma iInter₂_congr {s t : ∀ i, κ i → Set α} (h : ∀ i j, s i j = t i j) :
⋂ (i) (j), s i j = ⋂ (i) (j), t i j :=
iInter_congr fun i => iInter_congr <| h i
section Nonempty
variable [Nonempty ι] {f : ι → Set α} {s : Set α}
lemma iUnion_const (s : Set β) : ⋃ _ : ι, s = s := iSup_const
lemma iInter_const (s : Set β) : ⋂ _ : ι, s = s := iInf_const
lemma iUnion_eq_const (hf : ∀ i, f i = s) : ⋃ i, f i = s :=
(iUnion_congr hf).trans <| iUnion_const _
lemma iInter_eq_const (hf : ∀ i, f i = s) : ⋂ i, f i = s :=
(iInter_congr hf).trans <| iInter_const _
end Nonempty
@[simp]
theorem compl_iUnion (s : ι → Set β) : (⋃ i, s i)ᶜ = ⋂ i, (s i)ᶜ :=
compl_iSup
theorem compl_iUnion₂ (s : ∀ i, κ i → Set α) : (⋃ (i) (j), s i j)ᶜ = ⋂ (i) (j), (s i j)ᶜ := by
simp_rw [compl_iUnion]
@[simp]
theorem compl_iInter (s : ι → Set β) : (⋂ i, s i)ᶜ = ⋃ i, (s i)ᶜ :=
compl_iInf
theorem compl_iInter₂ (s : ∀ i, κ i → Set α) : (⋂ (i) (j), s i j)ᶜ = ⋃ (i) (j), (s i j)ᶜ := by
simp_rw [compl_iInter]
-- classical -- complete_boolean_algebra
theorem iUnion_eq_compl_iInter_compl (s : ι → Set β) : ⋃ i, s i = (⋂ i, (s i)ᶜ)ᶜ := by
simp only [compl_iInter, compl_compl]
-- classical -- complete_boolean_algebra
theorem iInter_eq_compl_iUnion_compl (s : ι → Set β) : ⋂ i, s i = (⋃ i, (s i)ᶜ)ᶜ := by
simp only [compl_iUnion, compl_compl]
theorem inter_iUnion (s : Set β) (t : ι → Set β) : (s ∩ ⋃ i, t i) = ⋃ i, s ∩ t i :=
inf_iSup_eq _ _
theorem iUnion_inter (s : Set β) (t : ι → Set β) : (⋃ i, t i) ∩ s = ⋃ i, t i ∩ s :=
iSup_inf_eq _ _
theorem iUnion_union_distrib (s : ι → Set β) (t : ι → Set β) :
⋃ i, s i ∪ t i = (⋃ i, s i) ∪ ⋃ i, t i :=
iSup_sup_eq
theorem iInter_inter_distrib (s : ι → Set β) (t : ι → Set β) :
⋂ i, s i ∩ t i = (⋂ i, s i) ∩ ⋂ i, t i :=
iInf_inf_eq
theorem union_iUnion [Nonempty ι] (s : Set β) (t : ι → Set β) : (s ∪ ⋃ i, t i) = ⋃ i, s ∪ t i :=
sup_iSup
theorem iUnion_union [Nonempty ι] (s : Set β) (t : ι → Set β) : (⋃ i, t i) ∪ s = ⋃ i, t i ∪ s :=
iSup_sup
theorem inter_iInter [Nonempty ι] (s : Set β) (t : ι → Set β) : (s ∩ ⋂ i, t i) = ⋂ i, s ∩ t i :=
inf_iInf
theorem iInter_inter [Nonempty ι] (s : Set β) (t : ι → Set β) : (⋂ i, t i) ∩ s = ⋂ i, t i ∩ s :=
iInf_inf
theorem insert_iUnion [Nonempty ι] (x : β) (t : ι → Set β) :
insert x (⋃ i, t i) = ⋃ i, insert x (t i) := by
simp_rw [← union_singleton, iUnion_union]
-- classical
theorem union_iInter (s : Set β) (t : ι → Set β) : (s ∪ ⋂ i, t i) = ⋂ i, s ∪ t i :=
sup_iInf_eq _ _
theorem iInter_union (s : ι → Set β) (t : Set β) : (⋂ i, s i) ∪ t = ⋂ i, s i ∪ t :=
iInf_sup_eq _ _
theorem insert_iInter (x : β) (t : ι → Set β) : insert x (⋂ i, t i) = ⋂ i, insert x (t i) := by
simp_rw [← union_singleton, iInter_union]
theorem iUnion_diff (s : Set β) (t : ι → Set β) : (⋃ i, t i) \ s = ⋃ i, t i \ s :=
iUnion_inter _ _
theorem diff_iUnion [Nonempty ι] (s : Set β) (t : ι → Set β) : (s \ ⋃ i, t i) = ⋂ i, s \ t i := by
rw [diff_eq, compl_iUnion, inter_iInter]; rfl
theorem diff_iInter (s : Set β) (t : ι → Set β) : (s \ ⋂ i, t i) = ⋃ i, s \ t i := by
rw [diff_eq, compl_iInter, inter_iUnion]; rfl
theorem iUnion_inter_subset {ι α} {s t : ι → Set α} : ⋃ i, s i ∩ t i ⊆ (⋃ i, s i) ∩ ⋃ i, t i :=
le_iSup_inf_iSup s t
theorem iUnion_inter_of_monotone {ι α} [Preorder ι] [IsDirected ι (· ≤ ·)] {s t : ι → Set α}
(hs : Monotone s) (ht : Monotone t) : ⋃ i, s i ∩ t i = (⋃ i, s i) ∩ ⋃ i, t i :=
iSup_inf_of_monotone hs ht
theorem iUnion_inter_of_antitone {ι α} [Preorder ι] [IsDirected ι (swap (· ≤ ·))] {s t : ι → Set α}
(hs : Antitone s) (ht : Antitone t) : ⋃ i, s i ∩ t i = (⋃ i, s i) ∩ ⋃ i, t i :=
iSup_inf_of_antitone hs ht
theorem iInter_union_of_monotone {ι α} [Preorder ι] [IsDirected ι (swap (· ≤ ·))] {s t : ι → Set α}
(hs : Monotone s) (ht : Monotone t) : ⋂ i, s i ∪ t i = (⋂ i, s i) ∪ ⋂ i, t i :=
iInf_sup_of_monotone hs ht
theorem iInter_union_of_antitone {ι α} [Preorder ι] [IsDirected ι (· ≤ ·)] {s t : ι → Set α}
(hs : Antitone s) (ht : Antitone t) : ⋂ i, s i ∪ t i = (⋂ i, s i) ∪ ⋂ i, t i :=
iInf_sup_of_antitone hs ht
/-- An equality version of this lemma is `iUnion_iInter_of_monotone` in `Data.Set.Finite`. -/
theorem iUnion_iInter_subset {s : ι → ι' → Set α} : (⋃ j, ⋂ i, s i j) ⊆ ⋂ i, ⋃ j, s i j :=
iSup_iInf_le_iInf_iSup (flip s)
theorem iUnion_option {ι} (s : Option ι → Set α) : ⋃ o, s o = s none ∪ ⋃ i, s (some i) :=
iSup_option s
theorem iInter_option {ι} (s : Option ι → Set α) : ⋂ o, s o = s none ∩ ⋂ i, s (some i) :=
iInf_option s
section
variable (p : ι → Prop) [DecidablePred p]
theorem iUnion_dite (f : ∀ i, p i → Set α) (g : ∀ i, ¬p i → Set α) :
⋃ i, (if h : p i then f i h else g i h) = (⋃ (i) (h : p i), f i h) ∪ ⋃ (i) (h : ¬p i), g i h :=
iSup_dite _ _ _
theorem iUnion_ite (f g : ι → Set α) :
⋃ i, (if p i then f i else g i) = (⋃ (i) (_ : p i), f i) ∪ ⋃ (i) (_ : ¬p i), g i :=
iUnion_dite _ _ _
theorem iInter_dite (f : ∀ i, p i → Set α) (g : ∀ i, ¬p i → Set α) :
⋂ i, (if h : p i then f i h else g i h) = (⋂ (i) (h : p i), f i h) ∩ ⋂ (i) (h : ¬p i), g i h :=
iInf_dite _ _ _
theorem iInter_ite (f g : ι → Set α) :
⋂ i, (if p i then f i else g i) = (⋂ (i) (_ : p i), f i) ∩ ⋂ (i) (_ : ¬p i), g i :=
iInter_dite _ _ _
end
/-! ### Unions and intersections indexed by `Prop` -/
theorem iInter_false {s : False → Set α} : iInter s = univ :=
iInf_false
theorem iUnion_false {s : False → Set α} : iUnion s = ∅ :=
iSup_false
@[simp]
theorem iInter_true {s : True → Set α} : iInter s = s trivial :=
iInf_true
@[simp]
theorem iUnion_true {s : True → Set α} : iUnion s = s trivial :=
iSup_true
@[simp]
theorem iInter_exists {p : ι → Prop} {f : Exists p → Set α} :
⋂ x, f x = ⋂ (i) (h : p i), f ⟨i, h⟩ :=
iInf_exists
@[simp]
theorem iUnion_exists {p : ι → Prop} {f : Exists p → Set α} :
⋃ x, f x = ⋃ (i) (h : p i), f ⟨i, h⟩ :=
iSup_exists
@[simp]
theorem iUnion_empty : (⋃ _ : ι, ∅ : Set α) = ∅ :=
iSup_bot
@[simp]
theorem iInter_univ : (⋂ _ : ι, univ : Set α) = univ :=
iInf_top
section
variable {s : ι → Set α}
@[simp]
theorem iUnion_eq_empty : ⋃ i, s i = ∅ ↔ ∀ i, s i = ∅ :=
iSup_eq_bot
@[simp]
theorem iInter_eq_univ : ⋂ i, s i = univ ↔ ∀ i, s i = univ :=
iInf_eq_top
@[simp]
theorem nonempty_iUnion : (⋃ i, s i).Nonempty ↔ ∃ i, (s i).Nonempty := by
simp [nonempty_iff_ne_empty]
theorem nonempty_biUnion {t : Set α} {s : α → Set β} :
(⋃ i ∈ t, s i).Nonempty ↔ ∃ i ∈ t, (s i).Nonempty := by simp
theorem iUnion_nonempty_index (s : Set α) (t : s.Nonempty → Set β) :
⋃ h, t h = ⋃ x ∈ s, t ⟨x, ‹_›⟩ :=
iSup_exists
end
@[simp]
theorem iInter_iInter_eq_left {b : β} {s : ∀ x : β, x = b → Set α} :
⋂ (x) (h : x = b), s x h = s b rfl :=
iInf_iInf_eq_left
@[simp]
theorem iInter_iInter_eq_right {b : β} {s : ∀ x : β, b = x → Set α} :
⋂ (x) (h : b = x), s x h = s b rfl :=
iInf_iInf_eq_right
@[simp]
theorem iUnion_iUnion_eq_left {b : β} {s : ∀ x : β, x = b → Set α} :
⋃ (x) (h : x = b), s x h = s b rfl :=
iSup_iSup_eq_left
@[simp]
theorem iUnion_iUnion_eq_right {b : β} {s : ∀ x : β, b = x → Set α} :
⋃ (x) (h : b = x), s x h = s b rfl :=
iSup_iSup_eq_right
theorem iInter_or {p q : Prop} (s : p ∨ q → Set α) :
⋂ h, s h = (⋂ h : p, s (Or.inl h)) ∩ ⋂ h : q, s (Or.inr h) :=
iInf_or
theorem iUnion_or {p q : Prop} (s : p ∨ q → Set α) :
⋃ h, s h = (⋃ i, s (Or.inl i)) ∪ ⋃ j, s (Or.inr j) :=
iSup_or
theorem iUnion_and {p q : Prop} (s : p ∧ q → Set α) : ⋃ h, s h = ⋃ (hp) (hq), s ⟨hp, hq⟩ :=
iSup_and
theorem iInter_and {p q : Prop} (s : p ∧ q → Set α) : ⋂ h, s h = ⋂ (hp) (hq), s ⟨hp, hq⟩ :=
iInf_and
theorem iUnion_comm (s : ι → ι' → Set α) : ⋃ (i) (i'), s i i' = ⋃ (i') (i), s i i' :=
iSup_comm
theorem iInter_comm (s : ι → ι' → Set α) : ⋂ (i) (i'), s i i' = ⋂ (i') (i), s i i' :=
iInf_comm
theorem iUnion_sigma {γ : α → Type*} (s : Sigma γ → Set β) : ⋃ ia, s ia = ⋃ i, ⋃ a, s ⟨i, a⟩ :=
iSup_sigma
theorem iUnion_sigma' {γ : α → Type*} (s : ∀ i, γ i → Set β) :
⋃ i, ⋃ a, s i a = ⋃ ia : Sigma γ, s ia.1 ia.2 :=
iSup_sigma' _
theorem iInter_sigma {γ : α → Type*} (s : Sigma γ → Set β) : ⋂ ia, s ia = ⋂ i, ⋂ a, s ⟨i, a⟩ :=
iInf_sigma
theorem iInter_sigma' {γ : α → Type*} (s : ∀ i, γ i → Set β) :
⋂ i, ⋂ a, s i a = ⋂ ia : Sigma γ, s ia.1 ia.2 :=
iInf_sigma' _
theorem iUnion₂_comm (s : ∀ i₁, κ₁ i₁ → ∀ i₂, κ₂ i₂ → Set α) :
⋃ (i₁) (j₁) (i₂) (j₂), s i₁ j₁ i₂ j₂ = ⋃ (i₂) (j₂) (i₁) (j₁), s i₁ j₁ i₂ j₂ :=
iSup₂_comm _
theorem iInter₂_comm (s : ∀ i₁, κ₁ i₁ → ∀ i₂, κ₂ i₂ → Set α) :
⋂ (i₁) (j₁) (i₂) (j₂), s i₁ j₁ i₂ j₂ = ⋂ (i₂) (j₂) (i₁) (j₁), s i₁ j₁ i₂ j₂ :=
iInf₂_comm _
@[simp]
theorem biUnion_and (p : ι → Prop) (q : ι → ι' → Prop) (s : ∀ x y, p x ∧ q x y → Set α) :
⋃ (x : ι) (y : ι') (h : p x ∧ q x y), s x y h =
⋃ (x : ι) (hx : p x) (y : ι') (hy : q x y), s x y ⟨hx, hy⟩ := by
simp only [iUnion_and, @iUnion_comm _ ι']
@[simp]
theorem biUnion_and' (p : ι' → Prop) (q : ι → ι' → Prop) (s : ∀ x y, p y ∧ q x y → Set α) :
⋃ (x : ι) (y : ι') (h : p y ∧ q x y), s x y h =
⋃ (y : ι') (hy : p y) (x : ι) (hx : q x y), s x y ⟨hy, hx⟩ := by
simp only [iUnion_and, @iUnion_comm _ ι]
@[simp]
theorem biInter_and (p : ι → Prop) (q : ι → ι' → Prop) (s : ∀ x y, p x ∧ q x y → Set α) :
⋂ (x : ι) (y : ι') (h : p x ∧ q x y), s x y h =
⋂ (x : ι) (hx : p x) (y : ι') (hy : q x y), s x y ⟨hx, hy⟩ := by
simp only [iInter_and, @iInter_comm _ ι']
@[simp]
theorem biInter_and' (p : ι' → Prop) (q : ι → ι' → Prop) (s : ∀ x y, p y ∧ q x y → Set α) :
⋂ (x : ι) (y : ι') (h : p y ∧ q x y), s x y h =
⋂ (y : ι') (hy : p y) (x : ι) (hx : q x y), s x y ⟨hy, hx⟩ := by
simp only [iInter_and, @iInter_comm _ ι]
@[simp]
theorem iUnion_iUnion_eq_or_left {b : β} {p : β → Prop} {s : ∀ x : β, x = b ∨ p x → Set α} :
⋃ (x) (h), s x h = s b (Or.inl rfl) ∪ ⋃ (x) (h : p x), s x (Or.inr h) := by
simp only [iUnion_or, iUnion_union_distrib, iUnion_iUnion_eq_left]
@[simp]
theorem iInter_iInter_eq_or_left {b : β} {p : β → Prop} {s : ∀ x : β, x = b ∨ p x → Set α} :
⋂ (x) (h), s x h = s b (Or.inl rfl) ∩ ⋂ (x) (h : p x), s x (Or.inr h) := by
simp only [iInter_or, iInter_inter_distrib, iInter_iInter_eq_left]
lemma iUnion_sum {s : α ⊕ β → Set γ} : ⋃ x, s x = (⋃ x, s (.inl x)) ∪ ⋃ x, s (.inr x) := iSup_sum
lemma iInter_sum {s : α ⊕ β → Set γ} : ⋂ x, s x = (⋂ x, s (.inl x)) ∩ ⋂ x, s (.inr x) := iInf_sum
theorem iUnion_psigma {γ : α → Type*} (s : PSigma γ → Set β) : ⋃ ia, s ia = ⋃ i, ⋃ a, s ⟨i, a⟩ :=
iSup_psigma _
/-- A reversed version of `iUnion_psigma` with a curried map. -/
theorem iUnion_psigma' {γ : α → Type*} (s : ∀ i, γ i → Set β) :
⋃ i, ⋃ a, s i a = ⋃ ia : PSigma γ, s ia.1 ia.2 :=
iSup_psigma' _
theorem iInter_psigma {γ : α → Type*} (s : PSigma γ → Set β) : ⋂ ia, s ia = ⋂ i, ⋂ a, s ⟨i, a⟩ :=
iInf_psigma _
/-- A reversed version of `iInter_psigma` with a curried map. -/
theorem iInter_psigma' {γ : α → Type*} (s : ∀ i, γ i → Set β) :
⋂ i, ⋂ a, s i a = ⋂ ia : PSigma γ, s ia.1 ia.2 :=
iInf_psigma' _
/-! ### Bounded unions and intersections -/
/-- A specialization of `mem_iUnion₂`. -/
theorem mem_biUnion {s : Set α} {t : α → Set β} {x : α} {y : β} (xs : x ∈ s) (ytx : y ∈ t x) :
y ∈ ⋃ x ∈ s, t x :=
mem_iUnion₂_of_mem xs ytx
/-- A specialization of `mem_iInter₂`. -/
theorem mem_biInter {s : Set α} {t : α → Set β} {y : β} (h : ∀ x ∈ s, y ∈ t x) :
y ∈ ⋂ x ∈ s, t x :=
mem_iInter₂_of_mem h
/-- A specialization of `subset_iUnion₂`. -/
theorem subset_biUnion_of_mem {s : Set α} {u : α → Set β} {x : α} (xs : x ∈ s) :
u x ⊆ ⋃ x ∈ s, u x :=
subset_iUnion₂ (s := fun i _ => u i) x xs
/-- A specialization of `iInter₂_subset`. -/
theorem biInter_subset_of_mem {s : Set α} {t : α → Set β} {x : α} (xs : x ∈ s) :
⋂ x ∈ s, t x ⊆ t x :=
iInter₂_subset x xs
lemma biInter_subset_biUnion {s : Set α} (hs : s.Nonempty) {t : α → Set β} :
⋂ x ∈ s, t x ⊆ ⋃ x ∈ s, t x := biInf_le_biSup hs
theorem biUnion_subset_biUnion_left {s s' : Set α} {t : α → Set β} (h : s ⊆ s') :
⋃ x ∈ s, t x ⊆ ⋃ x ∈ s', t x :=
iUnion₂_subset fun _ hx => subset_biUnion_of_mem <| h hx
theorem biInter_subset_biInter_left {s s' : Set α} {t : α → Set β} (h : s' ⊆ s) :
⋂ x ∈ s, t x ⊆ ⋂ x ∈ s', t x :=
subset_iInter₂ fun _ hx => biInter_subset_of_mem <| h hx
theorem biUnion_mono {s s' : Set α} {t t' : α → Set β} (hs : s' ⊆ s) (h : ∀ x ∈ s, t x ⊆ t' x) :
⋃ x ∈ s', t x ⊆ ⋃ x ∈ s, t' x :=
(biUnion_subset_biUnion_left hs).trans <| iUnion₂_mono h
theorem biInter_mono {s s' : Set α} {t t' : α → Set β} (hs : s ⊆ s') (h : ∀ x ∈ s, t x ⊆ t' x) :
⋂ x ∈ s', t x ⊆ ⋂ x ∈ s, t' x :=
(biInter_subset_biInter_left hs).trans <| iInter₂_mono h
theorem biUnion_eq_iUnion (s : Set α) (t : ∀ x ∈ s, Set β) :
⋃ x ∈ s, t x ‹_› = ⋃ x : s, t x x.2 :=
iSup_subtype'
theorem biInter_eq_iInter (s : Set α) (t : ∀ x ∈ s, Set β) :
⋂ x ∈ s, t x ‹_› = ⋂ x : s, t x x.2 :=
iInf_subtype'
@[simp] lemma biUnion_const {s : Set α} (hs : s.Nonempty) (t : Set β) : ⋃ a ∈ s, t = t :=
biSup_const hs
@[simp] lemma biInter_const {s : Set α} (hs : s.Nonempty) (t : Set β) : ⋂ a ∈ s, t = t :=
biInf_const hs
theorem iUnion_subtype (p : α → Prop) (s : { x // p x } → Set β) :
⋃ x : { x // p x }, s x = ⋃ (x) (hx : p x), s ⟨x, hx⟩ :=
iSup_subtype
theorem iInter_subtype (p : α → Prop) (s : { x // p x } → Set β) :
⋂ x : { x // p x }, s x = ⋂ (x) (hx : p x), s ⟨x, hx⟩ :=
iInf_subtype
theorem biInter_empty (u : α → Set β) : ⋂ x ∈ (∅ : Set α), u x = univ :=
iInf_emptyset
theorem biInter_univ (u : α → Set β) : ⋂ x ∈ @univ α, u x = ⋂ x, u x :=
iInf_univ
@[simp]
theorem biUnion_self (s : Set α) : ⋃ x ∈ s, s = s :=
Subset.antisymm (iUnion₂_subset fun _ _ => Subset.refl s) fun _ hx => mem_biUnion hx hx
@[simp]
theorem iUnion_nonempty_self (s : Set α) : ⋃ _ : s.Nonempty, s = s := by
rw [iUnion_nonempty_index, biUnion_self]
theorem biInter_singleton (a : α) (s : α → Set β) : ⋂ x ∈ ({a} : Set α), s x = s a :=
iInf_singleton
theorem biInter_union (s t : Set α) (u : α → Set β) :
⋂ x ∈ s ∪ t, u x = (⋂ x ∈ s, u x) ∩ ⋂ x ∈ t, u x :=
iInf_union
theorem biInter_insert (a : α) (s : Set α) (t : α → Set β) :
⋂ x ∈ insert a s, t x = t a ∩ ⋂ x ∈ s, t x := by simp
theorem biInter_pair (a b : α) (s : α → Set β) : ⋂ x ∈ ({a, b} : Set α), s x = s a ∩ s b := by
rw [biInter_insert, biInter_singleton]
theorem biInter_inter {ι α : Type*} {s : Set ι} (hs : s.Nonempty) (f : ι → Set α) (t : Set α) :
⋂ i ∈ s, f i ∩ t = (⋂ i ∈ s, f i) ∩ t := by
haveI : Nonempty s := hs.to_subtype
simp [biInter_eq_iInter, ← iInter_inter]
theorem inter_biInter {ι α : Type*} {s : Set ι} (hs : s.Nonempty) (f : ι → Set α) (t : Set α) :
⋂ i ∈ s, t ∩ f i = t ∩ ⋂ i ∈ s, f i := by
rw [inter_comm, ← biInter_inter hs]
simp [inter_comm]
theorem biUnion_empty (s : α → Set β) : ⋃ x ∈ (∅ : Set α), s x = ∅ :=
iSup_emptyset
theorem biUnion_univ (s : α → Set β) : ⋃ x ∈ @univ α, s x = ⋃ x, s x :=
iSup_univ
theorem biUnion_singleton (a : α) (s : α → Set β) : ⋃ x ∈ ({a} : Set α), s x = s a :=
iSup_singleton
@[simp]
theorem biUnion_of_singleton (s : Set α) : ⋃ x ∈ s, {x} = s :=
ext <| by simp
theorem biUnion_union (s t : Set α) (u : α → Set β) :
⋃ x ∈ s ∪ t, u x = (⋃ x ∈ s, u x) ∪ ⋃ x ∈ t, u x :=
iSup_union
@[simp]
theorem iUnion_coe_set {α β : Type*} (s : Set α) (f : s → Set β) :
⋃ i, f i = ⋃ i ∈ s, f ⟨i, ‹i ∈ s›⟩ :=
iUnion_subtype _ _
@[simp]
theorem iInter_coe_set {α β : Type*} (s : Set α) (f : s → Set β) :
⋂ i, f i = ⋂ i ∈ s, f ⟨i, ‹i ∈ s›⟩ :=
iInter_subtype _ _
theorem biUnion_insert (a : α) (s : Set α) (t : α → Set β) :
⋃ x ∈ insert a s, t x = t a ∪ ⋃ x ∈ s, t x := by simp
theorem biUnion_pair (a b : α) (s : α → Set β) : ⋃ x ∈ ({a, b} : Set α), s x = s a ∪ s b := by
simp
theorem inter_iUnion₂ (s : Set α) (t : ∀ i, κ i → Set α) :
(s ∩ ⋃ (i) (j), t i j) = ⋃ (i) (j), s ∩ t i j := by simp only [inter_iUnion]
theorem iUnion₂_inter (s : ∀ i, κ i → Set α) (t : Set α) :
(⋃ (i) (j), s i j) ∩ t = ⋃ (i) (j), s i j ∩ t := by simp_rw [iUnion_inter]
theorem union_iInter₂ (s : Set α) (t : ∀ i, κ i → Set α) :
(s ∪ ⋂ (i) (j), t i j) = ⋂ (i) (j), s ∪ t i j := by simp_rw [union_iInter]
theorem iInter₂_union (s : ∀ i, κ i → Set α) (t : Set α) :
(⋂ (i) (j), s i j) ∪ t = ⋂ (i) (j), s i j ∪ t := by simp_rw [iInter_union]
theorem mem_sUnion_of_mem {x : α} {t : Set α} {S : Set (Set α)} (hx : x ∈ t) (ht : t ∈ S) :
x ∈ ⋃₀ S :=
⟨t, ht, hx⟩
-- is this theorem really necessary?
theorem not_mem_of_not_mem_sUnion {x : α} {t : Set α} {S : Set (Set α)} (hx : x ∉ ⋃₀ S)
(ht : t ∈ S) : x ∉ t := fun h => hx ⟨t, ht, h⟩
theorem sInter_subset_of_mem {S : Set (Set α)} {t : Set α} (tS : t ∈ S) : ⋂₀ S ⊆ t :=
sInf_le tS
theorem subset_sUnion_of_mem {S : Set (Set α)} {t : Set α} (tS : t ∈ S) : t ⊆ ⋃₀ S :=
le_sSup tS
theorem subset_sUnion_of_subset {s : Set α} (t : Set (Set α)) (u : Set α) (h₁ : s ⊆ u)
(h₂ : u ∈ t) : s ⊆ ⋃₀ t :=
Subset.trans h₁ (subset_sUnion_of_mem h₂)
theorem sUnion_subset {S : Set (Set α)} {t : Set α} (h : ∀ t' ∈ S, t' ⊆ t) : ⋃₀ S ⊆ t :=
sSup_le h
@[simp]
theorem sUnion_subset_iff {s : Set (Set α)} {t : Set α} : ⋃₀ s ⊆ t ↔ ∀ t' ∈ s, t' ⊆ t :=
sSup_le_iff
/-- `sUnion` is monotone under taking a subset of each set. -/
lemma sUnion_mono_subsets {s : Set (Set α)} {f : Set α → Set α} (hf : ∀ t : Set α, t ⊆ f t) :
⋃₀ s ⊆ ⋃₀ (f '' s) :=
fun _ ⟨t, htx, hxt⟩ ↦ ⟨f t, mem_image_of_mem f htx, hf t hxt⟩
/-- `sUnion` is monotone under taking a superset of each set. -/
lemma sUnion_mono_supsets {s : Set (Set α)} {f : Set α → Set α} (hf : ∀ t : Set α, f t ⊆ t) :
⋃₀ (f '' s) ⊆ ⋃₀ s :=
-- If t ∈ f '' s is arbitrary; t = f u for some u : Set α.
fun _ ⟨_, ⟨u, hus, hut⟩, hxt⟩ ↦ ⟨u, hus, (hut ▸ hf u) hxt⟩
theorem subset_sInter {S : Set (Set α)} {t : Set α} (h : ∀ t' ∈ S, t ⊆ t') : t ⊆ ⋂₀ S :=
le_sInf h
@[simp]
theorem subset_sInter_iff {S : Set (Set α)} {t : Set α} : t ⊆ ⋂₀ S ↔ ∀ t' ∈ S, t ⊆ t' :=
le_sInf_iff
@[gcongr]
theorem sUnion_subset_sUnion {S T : Set (Set α)} (h : S ⊆ T) : ⋃₀ S ⊆ ⋃₀ T :=
sUnion_subset fun _ hs => subset_sUnion_of_mem (h hs)
@[gcongr]
theorem sInter_subset_sInter {S T : Set (Set α)} (h : S ⊆ T) : ⋂₀ T ⊆ ⋂₀ S :=
subset_sInter fun _ hs => sInter_subset_of_mem (h hs)
@[simp]
theorem sUnion_empty : ⋃₀ ∅ = (∅ : Set α) :=
sSup_empty
@[simp]
theorem sInter_empty : ⋂₀ ∅ = (univ : Set α) :=
sInf_empty
@[simp]
theorem sUnion_singleton (s : Set α) : ⋃₀ {s} = s :=
sSup_singleton
@[simp]
theorem sInter_singleton (s : Set α) : ⋂₀ {s} = s :=
sInf_singleton
@[simp]
theorem sUnion_eq_empty {S : Set (Set α)} : ⋃₀ S = ∅ ↔ ∀ s ∈ S, s = ∅ :=
sSup_eq_bot
@[simp]
theorem sInter_eq_univ {S : Set (Set α)} : ⋂₀ S = univ ↔ ∀ s ∈ S, s = univ :=
sInf_eq_top
theorem subset_powerset_iff {s : Set (Set α)} {t : Set α} : s ⊆ 𝒫 t ↔ ⋃₀ s ⊆ t :=
sUnion_subset_iff.symm
/-- `⋃₀` and `𝒫` form a Galois connection. -/
theorem sUnion_powerset_gc :
GaloisConnection (⋃₀ · : Set (Set α) → Set α) (𝒫 · : Set α → Set (Set α)) :=
gc_sSup_Iic
/-- `⋃₀` and `𝒫` form a Galois insertion. -/
def sUnionPowersetGI :
GaloisInsertion (⋃₀ · : Set (Set α) → Set α) (𝒫 · : Set α → Set (Set α)) :=
gi_sSup_Iic
@[deprecated (since := "2024-12-07")] alias sUnion_powerset_gi := sUnionPowersetGI
/-- If all sets in a collection are either `∅` or `Set.univ`, then so is their union. -/
theorem sUnion_mem_empty_univ {S : Set (Set α)} (h : S ⊆ {∅, univ}) :
⋃₀ S ∈ ({∅, univ} : Set (Set α)) := by
simp only [mem_insert_iff, mem_singleton_iff, or_iff_not_imp_left, sUnion_eq_empty, not_forall]
rintro ⟨s, hs, hne⟩
obtain rfl : s = univ := (h hs).resolve_left hne
exact univ_subset_iff.1 <| subset_sUnion_of_mem hs
@[simp]
theorem nonempty_sUnion {S : Set (Set α)} : (⋃₀ S).Nonempty ↔ ∃ s ∈ S, Set.Nonempty s := by
simp [nonempty_iff_ne_empty]
theorem Nonempty.of_sUnion {s : Set (Set α)} (h : (⋃₀ s).Nonempty) : s.Nonempty :=
let ⟨s, hs, _⟩ := nonempty_sUnion.1 h
⟨s, hs⟩
theorem Nonempty.of_sUnion_eq_univ [Nonempty α] {s : Set (Set α)} (h : ⋃₀ s = univ) : s.Nonempty :=
Nonempty.of_sUnion <| h.symm ▸ univ_nonempty
theorem sUnion_union (S T : Set (Set α)) : ⋃₀ (S ∪ T) = ⋃₀ S ∪ ⋃₀ T :=
sSup_union
theorem sInter_union (S T : Set (Set α)) : ⋂₀ (S ∪ T) = ⋂₀ S ∩ ⋂₀ T :=
sInf_union
@[simp]
theorem sUnion_insert (s : Set α) (T : Set (Set α)) : ⋃₀ insert s T = s ∪ ⋃₀ T :=
sSup_insert
@[simp]
theorem sInter_insert (s : Set α) (T : Set (Set α)) : ⋂₀ insert s T = s ∩ ⋂₀ T :=
sInf_insert
@[simp]
theorem sUnion_diff_singleton_empty (s : Set (Set α)) : ⋃₀ (s \ {∅}) = ⋃₀ s :=
sSup_diff_singleton_bot s
@[simp]
theorem sInter_diff_singleton_univ (s : Set (Set α)) : ⋂₀ (s \ {univ}) = ⋂₀ s :=
sInf_diff_singleton_top s
theorem sUnion_pair (s t : Set α) : ⋃₀ {s, t} = s ∪ t :=
sSup_pair
theorem sInter_pair (s t : Set α) : ⋂₀ {s, t} = s ∩ t :=
sInf_pair
@[simp]
theorem sUnion_image (f : α → Set β) (s : Set α) : ⋃₀ (f '' s) = ⋃ a ∈ s, f a :=
sSup_image
@[simp]
theorem sInter_image (f : α → Set β) (s : Set α) : ⋂₀ (f '' s) = ⋂ a ∈ s, f a :=
sInf_image
@[simp]
lemma sUnion_image2 (f : α → β → Set γ) (s : Set α) (t : Set β) :
⋃₀ (image2 f s t) = ⋃ (a ∈ s) (b ∈ t), f a b := sSup_image2
@[simp]
lemma sInter_image2 (f : α → β → Set γ) (s : Set α) (t : Set β) :
⋂₀ (image2 f s t) = ⋂ (a ∈ s) (b ∈ t), f a b := sInf_image2
@[simp]
theorem sUnion_range (f : ι → Set β) : ⋃₀ range f = ⋃ x, f x :=
rfl
@[simp]
theorem sInter_range (f : ι → Set β) : ⋂₀ range f = ⋂ x, f x :=
rfl
theorem iUnion_eq_univ_iff {f : ι → Set α} : ⋃ i, f i = univ ↔ ∀ x, ∃ i, x ∈ f i := by
simp only [eq_univ_iff_forall, mem_iUnion]
theorem iUnion₂_eq_univ_iff {s : ∀ i, κ i → Set α} :
⋃ (i) (j), s i j = univ ↔ ∀ a, ∃ i j, a ∈ s i j := by
simp only [iUnion_eq_univ_iff, mem_iUnion]
theorem sUnion_eq_univ_iff {c : Set (Set α)} : ⋃₀ c = univ ↔ ∀ a, ∃ b ∈ c, a ∈ b := by
simp only [eq_univ_iff_forall, mem_sUnion]
-- classical
theorem iInter_eq_empty_iff {f : ι → Set α} : ⋂ i, f i = ∅ ↔ ∀ x, ∃ i, x ∉ f i := by
simp [Set.eq_empty_iff_forall_not_mem]
-- classical
theorem iInter₂_eq_empty_iff {s : ∀ i, κ i → Set α} :
⋂ (i) (j), s i j = ∅ ↔ ∀ a, ∃ i j, a ∉ s i j := by
simp only [eq_empty_iff_forall_not_mem, mem_iInter, not_forall]
-- classical
theorem sInter_eq_empty_iff {c : Set (Set α)} : ⋂₀ c = ∅ ↔ ∀ a, ∃ b ∈ c, a ∉ b := by
simp [Set.eq_empty_iff_forall_not_mem]
-- classical
@[simp]
theorem nonempty_iInter {f : ι → Set α} : (⋂ i, f i).Nonempty ↔ ∃ x, ∀ i, x ∈ f i := by
simp [nonempty_iff_ne_empty, iInter_eq_empty_iff]
-- classical
theorem nonempty_iInter₂ {s : ∀ i, κ i → Set α} :
(⋂ (i) (j), s i j).Nonempty ↔ ∃ a, ∀ i j, a ∈ s i j := by
simp
-- classical
@[simp]
theorem nonempty_sInter {c : Set (Set α)} : (⋂₀ c).Nonempty ↔ ∃ a, ∀ b ∈ c, a ∈ b := by
simp [nonempty_iff_ne_empty, sInter_eq_empty_iff]
-- classical
theorem compl_sUnion (S : Set (Set α)) : (⋃₀ S)ᶜ = ⋂₀ (compl '' S) :=
ext fun x => by simp
-- classical
theorem sUnion_eq_compl_sInter_compl (S : Set (Set α)) : ⋃₀ S = (⋂₀ (compl '' S))ᶜ := by
rw [← compl_compl (⋃₀ S), compl_sUnion]
-- classical
theorem compl_sInter (S : Set (Set α)) : (⋂₀ S)ᶜ = ⋃₀ (compl '' S) := by
rw [sUnion_eq_compl_sInter_compl, compl_compl_image]
-- classical
theorem sInter_eq_compl_sUnion_compl (S : Set (Set α)) : ⋂₀ S = (⋃₀ (compl '' S))ᶜ := by
rw [← compl_compl (⋂₀ S), compl_sInter]
theorem inter_empty_of_inter_sUnion_empty {s t : Set α} {S : Set (Set α)} (hs : t ∈ S)
(h : s ∩ ⋃₀ S = ∅) : s ∩ t = ∅ :=
eq_empty_of_subset_empty <| by
rw [← h]; exact inter_subset_inter_right _ (subset_sUnion_of_mem hs)
theorem range_sigma_eq_iUnion_range {γ : α → Type*} (f : Sigma γ → β) :
range f = ⋃ a, range fun b => f ⟨a, b⟩ :=
Set.ext <| by simp
theorem iUnion_eq_range_sigma (s : α → Set β) : ⋃ i, s i = range fun a : Σi, s i => a.2 := by
simp [Set.ext_iff]
theorem iUnion_eq_range_psigma (s : ι → Set β) : ⋃ i, s i = range fun a : Σ'i, s i => a.2 := by
simp [Set.ext_iff]
theorem iUnion_image_preimage_sigma_mk_eq_self {ι : Type*} {σ : ι → Type*} (s : Set (Sigma σ)) :
⋃ i, Sigma.mk i '' (Sigma.mk i ⁻¹' s) = s := by
ext x
simp only [mem_iUnion, mem_image, mem_preimage]
constructor
· rintro ⟨i, a, h, rfl⟩
exact h
· intro h
obtain ⟨i, a⟩ := x
exact ⟨i, a, h, rfl⟩
theorem Sigma.univ (X : α → Type*) : (Set.univ : Set (Σa, X a)) = ⋃ a, range (Sigma.mk a) :=
Set.ext fun x =>
iff_of_true trivial ⟨range (Sigma.mk x.1), Set.mem_range_self _, x.2, Sigma.eta x⟩
alias sUnion_mono := sUnion_subset_sUnion
alias sInter_mono := sInter_subset_sInter
theorem iUnion_subset_iUnion_const {s : Set α} (h : ι → ι₂) : ⋃ _ : ι, s ⊆ ⋃ _ : ι₂, s :=
iSup_const_mono (α := Set α) h
@[simp]
theorem iUnion_singleton_eq_range (f : α → β) : ⋃ x : α, {f x} = range f := by
ext x
simp [@eq_comm _ x]
theorem iUnion_insert_eq_range_union_iUnion {ι : Type*} (x : ι → β) (t : ι → Set β) :
⋃ i, insert (x i) (t i) = range x ∪ ⋃ i, t i := by
simp_rw [← union_singleton, iUnion_union_distrib, union_comm, iUnion_singleton_eq_range]
theorem iUnion_of_singleton (α : Type*) : (⋃ x, {x} : Set α) = univ := by simp [Set.ext_iff]
theorem iUnion_of_singleton_coe (s : Set α) : ⋃ i : s, ({(i : α)} : Set α) = s := by simp
theorem sUnion_eq_biUnion {s : Set (Set α)} : ⋃₀ s = ⋃ (i : Set α) (_ : i ∈ s), i := by
rw [← sUnion_image, image_id']
theorem sInter_eq_biInter {s : Set (Set α)} : ⋂₀ s = ⋂ (i : Set α) (_ : i ∈ s), i := by
rw [← sInter_image, image_id']
theorem sUnion_eq_iUnion {s : Set (Set α)} : ⋃₀ s = ⋃ i : s, i := by
simp only [← sUnion_range, Subtype.range_coe]
theorem sInter_eq_iInter {s : Set (Set α)} : ⋂₀ s = ⋂ i : s, i := by
simp only [← sInter_range, Subtype.range_coe]
@[simp]
theorem iUnion_of_empty [IsEmpty ι] (s : ι → Set α) : ⋃ i, s i = ∅ :=
iSup_of_empty _
@[simp]
theorem iInter_of_empty [IsEmpty ι] (s : ι → Set α) : ⋂ i, s i = univ :=
iInf_of_empty _
theorem union_eq_iUnion {s₁ s₂ : Set α} : s₁ ∪ s₂ = ⋃ b : Bool, cond b s₁ s₂ :=
sup_eq_iSup s₁ s₂
theorem inter_eq_iInter {s₁ s₂ : Set α} : s₁ ∩ s₂ = ⋂ b : Bool, cond b s₁ s₂ :=
inf_eq_iInf s₁ s₂
theorem sInter_union_sInter {S T : Set (Set α)} :
⋂₀ S ∪ ⋂₀ T = ⋂ p ∈ S ×ˢ T, (p : Set α × Set α).1 ∪ p.2 :=
sInf_sup_sInf
theorem sUnion_inter_sUnion {s t : Set (Set α)} :
⋃₀ s ∩ ⋃₀ t = ⋃ p ∈ s ×ˢ t, (p : Set α × Set α).1 ∩ p.2 :=
sSup_inf_sSup
theorem biUnion_iUnion (s : ι → Set α) (t : α → Set β) :
⋃ x ∈ ⋃ i, s i, t x = ⋃ (i) (x ∈ s i), t x := by simp [@iUnion_comm _ ι]
theorem biInter_iUnion (s : ι → Set α) (t : α → Set β) :
⋂ x ∈ ⋃ i, s i, t x = ⋂ (i) (x ∈ s i), t x := by simp [@iInter_comm _ ι]
theorem sUnion_iUnion (s : ι → Set (Set α)) : ⋃₀ ⋃ i, s i = ⋃ i, ⋃₀ s i := by
simp only [sUnion_eq_biUnion, biUnion_iUnion]
theorem sInter_iUnion (s : ι → Set (Set α)) : ⋂₀ ⋃ i, s i = ⋂ i, ⋂₀ s i := by
simp only [sInter_eq_biInter, biInter_iUnion]
theorem iUnion_range_eq_sUnion {α β : Type*} (C : Set (Set α)) {f : ∀ s : C, β → (s : Type _)}
(hf : ∀ s : C, Surjective (f s)) : ⋃ y : β, range (fun s : C => (f s y).val) = ⋃₀ C := by
ext x; constructor
· rintro ⟨s, ⟨y, rfl⟩, ⟨s, hs⟩, rfl⟩
refine ⟨_, hs, ?_⟩
exact (f ⟨s, hs⟩ y).2
· rintro ⟨s, hs, hx⟩
obtain ⟨y, hy⟩ := hf ⟨s, hs⟩ ⟨x, hx⟩
refine ⟨_, ⟨y, rfl⟩, ⟨s, hs⟩, ?_⟩
exact congr_arg Subtype.val hy
theorem iUnion_range_eq_iUnion (C : ι → Set α) {f : ∀ x : ι, β → C x}
(hf : ∀ x : ι, Surjective (f x)) : ⋃ y : β, range (fun x : ι => (f x y).val) = ⋃ x, C x := by
ext x; rw [mem_iUnion, mem_iUnion]; constructor
· rintro ⟨y, i, rfl⟩
exact ⟨i, (f i y).2⟩
· rintro ⟨i, hx⟩
obtain ⟨y, hy⟩ := hf i ⟨x, hx⟩
exact ⟨y, i, congr_arg Subtype.val hy⟩
theorem union_distrib_iInter_left (s : ι → Set α) (t : Set α) : (t ∪ ⋂ i, s i) = ⋂ i, t ∪ s i :=
sup_iInf_eq _ _
theorem union_distrib_iInter₂_left (s : Set α) (t : ∀ i, κ i → Set α) :
(s ∪ ⋂ (i) (j), t i j) = ⋂ (i) (j), s ∪ t i j := by simp_rw [union_distrib_iInter_left]
theorem union_distrib_iInter_right (s : ι → Set α) (t : Set α) : (⋂ i, s i) ∪ t = ⋂ i, s i ∪ t :=
iInf_sup_eq _ _
theorem union_distrib_iInter₂_right (s : ∀ i, κ i → Set α) (t : Set α) :
(⋂ (i) (j), s i j) ∪ t = ⋂ (i) (j), s i j ∪ t := by simp_rw [union_distrib_iInter_right]
lemma biUnion_lt_eq_iUnion [LT α] [NoMaxOrder α] {s : α → Set β} :
⋃ (n) (m < n), s m = ⋃ n, s n := biSup_lt_eq_iSup
lemma biUnion_le_eq_iUnion [Preorder α] {s : α → Set β} :
⋃ (n) (m ≤ n), s m = ⋃ n, s n := biSup_le_eq_iSup
lemma biInter_lt_eq_iInter [LT α] [NoMaxOrder α] {s : α → Set β} :
⋂ (n) (m < n), s m = ⋂ (n), s n := biInf_lt_eq_iInf
lemma biInter_le_eq_iInter [Preorder α] {s : α → Set β} :
⋂ (n) (m ≤ n), s m = ⋂ (n), s n := biInf_le_eq_iInf
lemma biUnion_gt_eq_iUnion [LT α] [NoMinOrder α] {s : α → Set β} :
⋃ (n) (m > n), s m = ⋃ n, s n := biSup_gt_eq_iSup
lemma biUnion_ge_eq_iUnion [Preorder α] {s : α → Set β} :
⋃ (n) (m ≥ n), s m = ⋃ n, s n := biSup_ge_eq_iSup
lemma biInter_gt_eq_iInf [LT α] [NoMinOrder α] {s : α → Set β} :
⋂ (n) (m > n), s m = ⋂ n, s n := biInf_gt_eq_iInf
lemma biInter_ge_eq_iInf [Preorder α] {s : α → Set β} :
⋂ (n) (m ≥ n), s m = ⋂ n, s n := biInf_ge_eq_iInf
section le
variable {ι : Type*} [PartialOrder ι] (s : ι → Set α) (i : ι)
theorem biUnion_le : (⋃ j ≤ i, s j) = (⋃ j < i, s j) ∪ s i :=
biSup_le_eq_sup s i
theorem biInter_le : (⋂ j ≤ i, s j) = (⋂ j < i, s j) ∩ s i :=
biInf_le_eq_inf s i
theorem biUnion_ge : (⋃ j ≥ i, s j) = s i ∪ ⋃ j > i, s j :=
biSup_ge_eq_sup s i
theorem biInter_ge : (⋂ j ≥ i, s j) = s i ∩ ⋂ j > i, s j :=
biInf_ge_eq_inf s i
end le
section Pi
variable {π : α → Type*}
theorem pi_def (i : Set α) (s : ∀ a, Set (π a)) : pi i s = ⋂ a ∈ i, eval a ⁻¹' s a := by
ext
simp
theorem univ_pi_eq_iInter (t : ∀ i, Set (π i)) : pi univ t = ⋂ i, eval i ⁻¹' t i := by
simp only [pi_def, iInter_true, mem_univ]
theorem pi_diff_pi_subset (i : Set α) (s t : ∀ a, Set (π a)) :
pi i s \ pi i t ⊆ ⋃ a ∈ i, eval a ⁻¹' (s a \ t a) := by
refine diff_subset_comm.2 fun x hx a ha => ?_
simp only [mem_diff, mem_pi, mem_iUnion, not_exists, mem_preimage, not_and, not_not,
eval_apply] at hx
exact hx.2 _ ha (hx.1 _ ha)
theorem iUnion_univ_pi {ι : α → Type*} (t : (a : α) → ι a → Set (π a)) :
⋃ x : (a : α) → ι a, pi univ (fun a => t a (x a)) = pi univ fun a => ⋃ j : ι a, t a j := by
ext
simp [Classical.skolem]
end Pi
section Directed
theorem directedOn_iUnion {r} {f : ι → Set α} (hd : Directed (· ⊆ ·) f)
(h : ∀ x, DirectedOn r (f x)) : DirectedOn r (⋃ x, f x) := by
simp only [DirectedOn, exists_prop, mem_iUnion, exists_imp]
exact fun a₁ b₁ fb₁ a₂ b₂ fb₂ =>
let ⟨z, zb₁, zb₂⟩ := hd b₁ b₂
let ⟨x, xf, xa₁, xa₂⟩ := h z a₁ (zb₁ fb₁) a₂ (zb₂ fb₂)
⟨x, ⟨z, xf⟩, xa₁, xa₂⟩
theorem directedOn_sUnion {r} {S : Set (Set α)} (hd : DirectedOn (· ⊆ ·) S)
(h : ∀ x ∈ S, DirectedOn r x) : DirectedOn r (⋃₀ S) := by
rw [sUnion_eq_iUnion]
exact directedOn_iUnion (directedOn_iff_directed.mp hd) (fun i ↦ h i.1 i.2)
theorem pairwise_iUnion₂ {S : Set (Set α)} (hd : DirectedOn (· ⊆ ·) S)
(r : α → α → Prop) (h : ∀ s ∈ S, s.Pairwise r) : (⋃ s ∈ S, s).Pairwise r := by
simp only [Set.Pairwise, Set.mem_iUnion, exists_prop, forall_exists_index, and_imp]
intro x S hS hx y T hT hy hne
obtain ⟨U, hU, hSU, hTU⟩ := hd S hS T hT
exact h U hU (hSU hx) (hTU hy) hne
end Directed
end Set
namespace Function
namespace Surjective
theorem iUnion_comp {f : ι → ι₂} (hf : Surjective f) (g : ι₂ → Set α) : ⋃ x, g (f x) = ⋃ y, g y :=
hf.iSup_comp g
theorem iInter_comp {f : ι → ι₂} (hf : Surjective f) (g : ι₂ → Set α) : ⋂ x, g (f x) = ⋂ y, g y :=
hf.iInf_comp g
end Surjective
end Function
/-!
### Disjoint sets
-/
section Disjoint
variable {s t : Set α}
namespace Set
@[simp]
theorem disjoint_iUnion_left {ι : Sort*} {s : ι → Set α} :
Disjoint (⋃ i, s i) t ↔ ∀ i, Disjoint (s i) t :=
iSup_disjoint_iff
@[simp]
theorem disjoint_iUnion_right {ι : Sort*} {s : ι → Set α} :
Disjoint t (⋃ i, s i) ↔ ∀ i, Disjoint t (s i) :=
disjoint_iSup_iff
theorem disjoint_iUnion₂_left {s : ∀ i, κ i → Set α} {t : Set α} :
Disjoint (⋃ (i) (j), s i j) t ↔ ∀ i j, Disjoint (s i j) t :=
iSup₂_disjoint_iff
theorem disjoint_iUnion₂_right {s : Set α} {t : ∀ i, κ i → Set α} :
Disjoint s (⋃ (i) (j), t i j) ↔ ∀ i j, Disjoint s (t i j) :=
disjoint_iSup₂_iff
@[simp]
theorem disjoint_sUnion_left {S : Set (Set α)} {t : Set α} :
Disjoint (⋃₀ S) t ↔ ∀ s ∈ S, Disjoint s t :=
sSup_disjoint_iff
@[simp]
theorem disjoint_sUnion_right {s : Set α} {S : Set (Set α)} :
Disjoint s (⋃₀ S) ↔ ∀ t ∈ S, Disjoint s t :=
disjoint_sSup_iff
lemma biUnion_compl_eq_of_pairwise_disjoint_of_iUnion_eq_univ {ι : Type*} {Es : ι → Set α}
(Es_union : ⋃ i, Es i = univ) (Es_disj : Pairwise fun i j ↦ Disjoint (Es i) (Es j))
(I : Set ι) :
(⋃ i ∈ I, Es i)ᶜ = ⋃ i ∈ Iᶜ, Es i := by
ext x
obtain ⟨i, hix⟩ : ∃ i, x ∈ Es i := by simp [← mem_iUnion, Es_union]
have obs : ∀ (J : Set ι), x ∈ ⋃ j ∈ J, Es j ↔ i ∈ J := by
refine fun J ↦ ⟨?_, fun i_in_J ↦ by simpa only [mem_iUnion, exists_prop] using ⟨i, i_in_J, hix⟩⟩
intro x_in_U
simp only [mem_iUnion, exists_prop] at x_in_U
obtain ⟨j, j_in_J, hjx⟩ := x_in_U
rwa [show i = j by by_contra i_ne_j; exact Disjoint.ne_of_mem (Es_disj i_ne_j) hix hjx rfl]
have obs' : ∀ (J : Set ι), x ∈ (⋃ j ∈ J, Es j)ᶜ ↔ i ∉ J :=
fun J ↦ by simpa only [mem_compl_iff, not_iff_not] using obs J
rw [obs, obs', mem_compl_iff]
end Set
end Disjoint
/-! ### Intervals -/
namespace Set
lemma nonempty_iInter_Iic_iff [Preorder α] {f : ι → α} :
(⋂ i, Iic (f i)).Nonempty ↔ BddBelow (range f) := by
have : (⋂ (i : ι), Iic (f i)) = lowerBounds (range f) := by
ext c; simp [lowerBounds]
simp [this, BddBelow]
lemma nonempty_iInter_Ici_iff [Preorder α] {f : ι → α} :
(⋂ i, Ici (f i)).Nonempty ↔ BddAbove (range f) :=
nonempty_iInter_Iic_iff (α := αᵒᵈ)
variable [CompleteLattice α]
theorem Ici_iSup (f : ι → α) : Ici (⨆ i, f i) = ⋂ i, Ici (f i) :=
ext fun _ => by simp only [mem_Ici, iSup_le_iff, mem_iInter]
theorem Iic_iInf (f : ι → α) : Iic (⨅ i, f i) = ⋂ i, Iic (f i) :=
ext fun _ => by simp only [mem_Iic, le_iInf_iff, mem_iInter]
theorem Ici_iSup₂ (f : ∀ i, κ i → α) : Ici (⨆ (i) (j), f i j) = ⋂ (i) (j), Ici (f i j) := by
simp_rw [Ici_iSup]
theorem Iic_iInf₂ (f : ∀ i, κ i → α) : Iic (⨅ (i) (j), f i j) = ⋂ (i) (j), Iic (f i j) := by
simp_rw [Iic_iInf]
theorem Ici_sSup (s : Set α) : Ici (sSup s) = ⋂ a ∈ s, Ici a := by rw [sSup_eq_iSup, Ici_iSup₂]
theorem Iic_sInf (s : Set α) : Iic (sInf s) = ⋂ a ∈ s, Iic a := by rw [sInf_eq_iInf, Iic_iInf₂]
end Set
namespace Set
variable (t : α → Set β)
theorem biUnion_diff_biUnion_subset (s₁ s₂ : Set α) :
((⋃ x ∈ s₁, t x) \ ⋃ x ∈ s₂, t x) ⊆ ⋃ x ∈ s₁ \ s₂, t x := by
simp only [diff_subset_iff, ← biUnion_union]
apply biUnion_subset_biUnion_left
rw [union_diff_self]
apply subset_union_right
/-- If `t` is an indexed family of sets, then there is a natural map from `Σ i, t i` to `⋃ i, t i`
sending `⟨i, x⟩` to `x`. -/
def sigmaToiUnion (x : Σi, t i) : ⋃ i, t i :=
⟨x.2, mem_iUnion.2 ⟨x.1, x.2.2⟩⟩
theorem sigmaToiUnion_surjective : Surjective (sigmaToiUnion t)
| ⟨b, hb⟩ =>
have : ∃ a, b ∈ t a := by simpa using hb
let ⟨a, hb⟩ := this
⟨⟨a, b, hb⟩, rfl⟩
theorem sigmaToiUnion_injective (h : Pairwise (Disjoint on t)) :
Injective (sigmaToiUnion t)
| ⟨a₁, b₁, h₁⟩, ⟨a₂, b₂, h₂⟩, eq =>
have b_eq : b₁ = b₂ := congr_arg Subtype.val eq
have a_eq : a₁ = a₂ :=
by_contradiction fun ne =>
have : b₁ ∈ t a₁ ∩ t a₂ := ⟨h₁, b_eq.symm ▸ h₂⟩
(h ne).le_bot this
Sigma.eq a_eq <| Subtype.eq <| by subst b_eq; subst a_eq; rfl
theorem sigmaToiUnion_bijective (h : Pairwise (Disjoint on t)) :
Bijective (sigmaToiUnion t) :=
⟨sigmaToiUnion_injective t h, sigmaToiUnion_surjective t⟩
/-- Equivalence from the disjoint union of a family of sets forming a partition of `β`, to `β`
itself. -/
noncomputable def sigmaEquiv (s : α → Set β) (hs : ∀ b, ∃! i, b ∈ s i) :
(Σ i, s i) ≃ β where
toFun | ⟨_, b⟩ => b
invFun b := ⟨(hs b).choose, b, (hs b).choose_spec.1⟩
left_inv | ⟨i, b, hb⟩ => Sigma.subtype_ext ((hs b).choose_spec.2 i hb).symm rfl
right_inv _ := rfl
/-- Equivalence between a disjoint union and a dependent sum. -/
noncomputable def unionEqSigmaOfDisjoint {t : α → Set β}
(h : Pairwise (Disjoint on t)) :
(⋃ i, t i) ≃ Σi, t i :=
(Equiv.ofBijective _ <| sigmaToiUnion_bijective t h).symm
theorem iUnion_ge_eq_iUnion_nat_add (u : ℕ → Set α) (n : ℕ) : ⋃ i ≥ n, u i = ⋃ i, u (i + n) :=
iSup_ge_eq_iSup_nat_add u n
theorem iInter_ge_eq_iInter_nat_add (u : ℕ → Set α) (n : ℕ) : ⋂ i ≥ n, u i = ⋂ i, u (i + n) :=
iInf_ge_eq_iInf_nat_add u n
theorem _root_.Monotone.iUnion_nat_add {f : ℕ → Set α} (hf : Monotone f) (k : ℕ) :
⋃ n, f (n + k) = ⋃ n, f n :=
hf.iSup_nat_add k
theorem _root_.Antitone.iInter_nat_add {f : ℕ → Set α} (hf : Antitone f) (k : ℕ) :
⋂ n, f (n + k) = ⋂ n, f n :=
hf.iInf_nat_add k
@[simp]
theorem iUnion_iInter_ge_nat_add (f : ℕ → Set α) (k : ℕ) :
⋃ n, ⋂ i ≥ n, f (i + k) = ⋃ n, ⋂ i ≥ n, f i :=
iSup_iInf_ge_nat_add f k
theorem union_iUnion_nat_succ (u : ℕ → Set α) : (u 0 ∪ ⋃ i, u (i + 1)) = ⋃ i, u i :=
sup_iSup_nat_succ u
theorem inter_iInter_nat_succ (u : ℕ → Set α) : (u 0 ∩ ⋂ i, u (i + 1)) = ⋂ i, u i :=
inf_iInf_nat_succ u
end Set
open Set
variable [CompleteLattice β]
theorem iSup_iUnion (s : ι → Set α) (f : α → β) : ⨆ a ∈ ⋃ i, s i, f a = ⨆ (i) (a ∈ s i), f a := by
rw [iSup_comm]
simp_rw [mem_iUnion, iSup_exists]
theorem iInf_iUnion (s : ι → Set α) (f : α → β) : ⨅ a ∈ ⋃ i, s i, f a = ⨅ (i) (a ∈ s i), f a :=
iSup_iUnion (β := βᵒᵈ) s f
theorem sSup_iUnion (t : ι → Set β) : sSup (⋃ i, t i) = ⨆ i, sSup (t i) := by
simp_rw [sSup_eq_iSup, iSup_iUnion]
theorem sSup_sUnion (s : Set (Set β)) : sSup (⋃₀ s) = ⨆ t ∈ s, sSup t := by
simp only [sUnion_eq_biUnion, sSup_eq_iSup, iSup_iUnion]
| Mathlib/Data/Set/Lattice.lean | 1,376 | 1,383 | theorem sInf_sUnion (s : Set (Set β)) : sInf (⋃₀ s) = ⨅ t ∈ s, sInf t :=
sSup_sUnion (β := βᵒᵈ) s
lemma iSup_sUnion (S : Set (Set α)) (f : α → β) :
(⨆ x ∈ ⋃₀ S, f x) = ⨆ (s ∈ S) (x ∈ s), f x := by | rw [sUnion_eq_iUnion, iSup_iUnion, ← iSup_subtype'']
lemma iInf_sUnion (S : Set (Set α)) (f : α → β) : |
/-
Copyright (c) 2021 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.ExpDeriv
import Mathlib.Analysis.SpecialFunctions.Complex.Circle
import Mathlib.Analysis.InnerProductSpace.l2Space
import Mathlib.MeasureTheory.Function.ContinuousMapDense
import Mathlib.MeasureTheory.Function.L2Space
import Mathlib.MeasureTheory.Group.Integral
import Mathlib.MeasureTheory.Integral.IntervalIntegral.Periodic
import Mathlib.Topology.ContinuousMap.StoneWeierstrass
import Mathlib.MeasureTheory.Integral.IntervalIntegral.IntegrationByParts
/-!
# Fourier analysis on the additive circle
This file contains basic results on Fourier series for functions on the additive circle
`AddCircle T = ℝ / ℤ • T`.
## Main definitions
* `haarAddCircle`, Haar measure on `AddCircle T`, normalized to have total measure `1`.
Note that this is not the same normalisation
as the standard measure defined in `IntervalIntegral.Periodic`,
so we do not declare it as a `MeasureSpace` instance, to avoid confusion.
* for `n : ℤ`, `fourier n` is the monomial `fun x => exp (2 π i n x / T)`,
bundled as a continuous map from `AddCircle T` to `ℂ`.
* `fourierBasis` is the Hilbert basis of `Lp ℂ 2 haarAddCircle` given by the images of the
monomials `fourier n`.
* `fourierCoeff f n`, for `f : AddCircle T → E` (with `E` a complete normed `ℂ`-vector space), is
the `n`-th Fourier coefficient of `f`, defined as an integral over `AddCircle T`. The lemma
`fourierCoeff_eq_intervalIntegral` expresses this as an integral over `[a, a + T]` for any real
`a`.
* `fourierCoeffOn`, for `f : ℝ → E` and `a < b` reals, is the `n`-th Fourier
coefficient of the unique periodic function of period `b - a` which agrees with `f` on `(a, b]`.
The lemma `fourierCoeffOn_eq_integral` expresses this as an integral over `[a, b]`.
## Main statements
The theorem `span_fourier_closure_eq_top` states that the span of the monomials `fourier n` is
dense in `C(AddCircle T, ℂ)`, i.e. that its `Submodule.topologicalClosure` is `⊤`. This follows
from the Stone-Weierstrass theorem after checking that the span is a subalgebra, is closed under
conjugation, and separates points.
Using this and general theory on approximation of Lᵖ functions by continuous functions, we deduce
(`span_fourierLp_closure_eq_top`) that for any `1 ≤ p < ∞`, the span of the Fourier monomials is
dense in the Lᵖ space of `AddCircle T`. For `p = 2` we show (`orthonormal_fourier`) that the
monomials are also orthonormal, so they form a Hilbert basis for L², which is named as
`fourierBasis`; in particular, for `L²` functions `f`, the Fourier series of `f` converges to `f`
in the `L²` topology (`hasSum_fourier_series_L2`). Parseval's identity, `tsum_sq_fourierCoeff`, is
a direct consequence.
For continuous maps `f : AddCircle T → ℂ`, the theorem
`hasSum_fourier_series_of_summable` states that if the sequence of Fourier
coefficients of `f` is summable, then the Fourier series `∑ (i : ℤ), fourierCoeff f i * fourier i`
converges to `f` in the uniform-convergence topology of `C(AddCircle T, ℂ)`.
-/
noncomputable section
open scoped ENNReal ComplexConjugate Real
open TopologicalSpace ContinuousMap MeasureTheory MeasureTheory.Measure Algebra Submodule Set
variable {T : ℝ}
namespace AddCircle
/-! ### Measure on `AddCircle T`
In this file we use the Haar measure on `AddCircle T` normalised to have total measure 1 (which is
**not** the same as the standard measure defined in `Topology.Instances.AddCircle`). -/
variable [hT : Fact (0 < T)]
/-- Haar measure on the additive circle, normalised to have total measure 1. -/
def haarAddCircle : Measure (AddCircle T) :=
addHaarMeasure ⊤
-- The `IsAddHaarMeasure` instance should be constructed by a deriving handler.
-- https://github.com/leanprover-community/mathlib4/issues/380
instance : IsAddHaarMeasure (@haarAddCircle T _) :=
Measure.isAddHaarMeasure_addHaarMeasure ⊤
instance : IsProbabilityMeasure (@haarAddCircle T _) :=
IsProbabilityMeasure.mk addHaarMeasure_self
theorem volume_eq_smul_haarAddCircle :
(volume : Measure (AddCircle T)) = ENNReal.ofReal T • (@haarAddCircle T _) :=
rfl
end AddCircle
open AddCircle
section Monomials
/-- The family of exponential monomials `fun x => exp (2 π i n x / T)`, parametrized by `n : ℤ` and
considered as bundled continuous maps from `ℝ / ℤ • T` to `ℂ`. -/
def fourier (n : ℤ) : C(AddCircle T, ℂ) where
toFun x := toCircle (n • x :)
continuous_toFun := continuous_induced_dom.comp <| continuous_toCircle.comp <| continuous_zsmul _
@[simp]
theorem fourier_apply {n : ℤ} {x : AddCircle T} : fourier n x = toCircle (n • x :) :=
rfl
-- simp normal form is `fourier_coe_apply'`
theorem fourier_coe_apply {n : ℤ} {x : ℝ} :
fourier n (x : AddCircle T) = Complex.exp (2 * π * Complex.I * n * x / T) := by
rw [fourier_apply, ← QuotientAddGroup.mk_zsmul, toCircle, Function.Periodic.lift_coe,
Circle.coe_exp, Complex.ofReal_mul, Complex.ofReal_div, Complex.ofReal_mul, zsmul_eq_mul,
Complex.ofReal_mul, Complex.ofReal_intCast]
norm_num
congr 1; ring
@[simp]
theorem fourier_coe_apply' {n : ℤ} {x : ℝ} :
toCircle (n • (x : AddCircle T) :) = Complex.exp (2 * π * Complex.I * n * x / T) := by
rw [← fourier_apply]; exact fourier_coe_apply
-- simp normal form is `fourier_zero'`
theorem fourier_zero {x : AddCircle T} : fourier 0 x = 1 := by
induction x using QuotientAddGroup.induction_on
simp only [fourier_coe_apply]
norm_num
theorem fourier_zero' {x : AddCircle T} : @toCircle T 0 = (1 : ℂ) := by
have : fourier 0 x = @toCircle T 0 := by rw [fourier_apply, zero_smul]
rw [← this]; exact fourier_zero
-- simp normal form is *also* `fourier_zero'`
theorem fourier_eval_zero (n : ℤ) : fourier n (0 : AddCircle T) = 1 := by
rw [← QuotientAddGroup.mk_zero, fourier_coe_apply, Complex.ofReal_zero, mul_zero,
zero_div, Complex.exp_zero]
theorem fourier_one {x : AddCircle T} : fourier 1 x = toCircle x := by rw [fourier_apply, one_zsmul]
-- simp normal form is `fourier_neg'`
| Mathlib/Analysis/Fourier/AddCircle.lean | 144 | 146 | theorem fourier_neg {n : ℤ} {x : AddCircle T} : fourier (-n) x = conj (fourier n x) := by | induction x using QuotientAddGroup.induction_on
simp_rw [fourier_apply, toCircle] |
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Analysis.SpecialFunctions.Trigonometric.Arctan
import Mathlib.Geometry.Euclidean.Angle.Unoriented.Affine
/-!
# Right-angled triangles
This file proves basic geometrical results about distances and angles in (possibly degenerate)
right-angled triangles in real inner product spaces and Euclidean affine spaces.
## Implementation notes
Results in this file are generally given in a form with only those non-degeneracy conditions
needed for the particular result, rather than requiring affine independence of the points of a
triangle unnecessarily.
## References
* https://en.wikipedia.org/wiki/Pythagorean_theorem
-/
noncomputable section
open scoped EuclideanGeometry
open scoped Real
open scoped RealInnerProductSpace
namespace InnerProductGeometry
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V]
/-- Pythagorean theorem, if-and-only-if vector angle form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two (x y : V) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ angle x y = π / 2 := by
rw [norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero]
exact inner_eq_zero_iff_angle_eq_pi_div_two x y
/-- Pythagorean theorem, vector angle form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq' (x y : V) (h : angle x y = π / 2) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ :=
(norm_add_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two x y).2 h
/-- Pythagorean theorem, subtracting vectors, if-and-only-if vector angle form. -/
theorem norm_sub_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two (x y : V) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ angle x y = π / 2 := by
rw [norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero]
exact inner_eq_zero_iff_angle_eq_pi_div_two x y
/-- Pythagorean theorem, subtracting vectors, vector angle form. -/
theorem norm_sub_sq_eq_norm_sq_add_norm_sq' (x y : V) (h : angle x y = π / 2) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ :=
(norm_sub_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two x y).2 h
/-- An angle in a right-angled triangle expressed using `arccos`. -/
theorem angle_add_eq_arccos_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
angle x (x + y) = Real.arccos (‖x‖ / ‖x + y‖) := by
rw [angle, inner_add_right, h, add_zero, real_inner_self_eq_norm_mul_norm]
by_cases hx : ‖x‖ = 0; · simp [hx]
rw [div_mul_eq_div_div, mul_self_div_self]
/-- An angle in a right-angled triangle expressed using `arcsin`. -/
theorem angle_add_eq_arcsin_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0 ∨ y ≠ 0) :
angle x (x + y) = Real.arcsin (‖y‖ / ‖x + y‖) := by
have hxy : ‖x + y‖ ^ 2 ≠ 0 := by
rw [pow_two, norm_add_sq_eq_norm_sq_add_norm_sq_real h, ne_comm]
refine ne_of_lt ?_
rcases h0 with (h0 | h0)
· exact
Left.add_pos_of_pos_of_nonneg (mul_self_pos.2 (norm_ne_zero_iff.2 h0)) (mul_self_nonneg _)
· exact
Left.add_pos_of_nonneg_of_pos (mul_self_nonneg _) (mul_self_pos.2 (norm_ne_zero_iff.2 h0))
rw [angle_add_eq_arccos_of_inner_eq_zero h,
Real.arccos_eq_arcsin (div_nonneg (norm_nonneg _) (norm_nonneg _)), div_pow, one_sub_div hxy]
nth_rw 1 [pow_two]
rw [norm_add_sq_eq_norm_sq_add_norm_sq_real h, pow_two, add_sub_cancel_left, ← pow_two, ← div_pow,
Real.sqrt_sq (div_nonneg (norm_nonneg _) (norm_nonneg _))]
/-- An angle in a right-angled triangle expressed using `arctan`. -/
theorem angle_add_eq_arctan_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0) :
angle x (x + y) = Real.arctan (‖y‖ / ‖x‖) := by
rw [angle_add_eq_arcsin_of_inner_eq_zero h (Or.inl h0), Real.arctan_eq_arcsin, ←
div_mul_eq_div_div, norm_add_eq_sqrt_iff_real_inner_eq_zero.2 h]
nth_rw 3 [← Real.sqrt_sq (norm_nonneg x)]
rw_mod_cast [← Real.sqrt_mul (sq_nonneg _), div_pow, pow_two, pow_two, mul_add, mul_one, mul_div,
mul_comm (‖x‖ * ‖x‖), ← mul_div, div_self (mul_self_pos.2 (norm_ne_zero_iff.2 h0)).ne', mul_one]
/-- An angle in a non-degenerate right-angled triangle is positive. -/
theorem angle_add_pos_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x = 0 ∨ y ≠ 0) :
0 < angle x (x + y) := by
rw [angle_add_eq_arccos_of_inner_eq_zero h, Real.arccos_pos,
norm_add_eq_sqrt_iff_real_inner_eq_zero.2 h]
by_cases hx : x = 0; · simp [hx]
rw [div_lt_one (Real.sqrt_pos.2 (Left.add_pos_of_pos_of_nonneg (mul_self_pos.2
(norm_ne_zero_iff.2 hx)) (mul_self_nonneg _))), Real.lt_sqrt (norm_nonneg _), pow_two]
simpa [hx] using h0
/-- An angle in a right-angled triangle is at most `π / 2`. -/
theorem angle_add_le_pi_div_two_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
angle x (x + y) ≤ π / 2 := by
rw [angle_add_eq_arccos_of_inner_eq_zero h, Real.arccos_le_pi_div_two]
exact div_nonneg (norm_nonneg _) (norm_nonneg _)
/-- An angle in a non-degenerate right-angled triangle is less than `π / 2`. -/
theorem angle_add_lt_pi_div_two_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0) :
angle x (x + y) < π / 2 := by
rw [angle_add_eq_arccos_of_inner_eq_zero h, Real.arccos_lt_pi_div_two,
norm_add_eq_sqrt_iff_real_inner_eq_zero.2 h]
exact div_pos (norm_pos_iff.2 h0) (Real.sqrt_pos.2 (Left.add_pos_of_pos_of_nonneg
(mul_self_pos.2 (norm_ne_zero_iff.2 h0)) (mul_self_nonneg _)))
/-- The cosine of an angle in a right-angled triangle as a ratio of sides. -/
theorem cos_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
Real.cos (angle x (x + y)) = ‖x‖ / ‖x + y‖ := by
rw [angle_add_eq_arccos_of_inner_eq_zero h,
Real.cos_arccos (le_trans (by norm_num) (div_nonneg (norm_nonneg _) (norm_nonneg _)))
(div_le_one_of_le₀ _ (norm_nonneg _))]
rw [mul_self_le_mul_self_iff (norm_nonneg _) (norm_nonneg _),
norm_add_sq_eq_norm_sq_add_norm_sq_real h]
exact le_add_of_nonneg_right (mul_self_nonneg _)
/-- The sine of an angle in a right-angled triangle as a ratio of sides. -/
theorem sin_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0 ∨ y ≠ 0) :
Real.sin (angle x (x + y)) = ‖y‖ / ‖x + y‖ := by
rw [angle_add_eq_arcsin_of_inner_eq_zero h h0,
Real.sin_arcsin (le_trans (by norm_num) (div_nonneg (norm_nonneg _) (norm_nonneg _)))
(div_le_one_of_le₀ _ (norm_nonneg _))]
rw [mul_self_le_mul_self_iff (norm_nonneg _) (norm_nonneg _),
norm_add_sq_eq_norm_sq_add_norm_sq_real h]
exact le_add_of_nonneg_left (mul_self_nonneg _)
/-- The tangent of an angle in a right-angled triangle as a ratio of sides. -/
theorem tan_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
Real.tan (angle x (x + y)) = ‖y‖ / ‖x‖ := by
by_cases h0 : x = 0; · simp [h0]
rw [angle_add_eq_arctan_of_inner_eq_zero h h0, Real.tan_arctan]
/-- The cosine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
adjacent side. -/
theorem cos_angle_add_mul_norm_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
Real.cos (angle x (x + y)) * ‖x + y‖ = ‖x‖ := by
rw [cos_angle_add_of_inner_eq_zero h]
by_cases hxy : ‖x + y‖ = 0
· have h' := norm_add_sq_eq_norm_sq_add_norm_sq_real h
rw [hxy, zero_mul, eq_comm,
add_eq_zero_iff_of_nonneg (mul_self_nonneg ‖x‖) (mul_self_nonneg ‖y‖), mul_self_eq_zero] at h'
simp [h'.1]
· exact div_mul_cancel₀ _ hxy
/-- The sine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
opposite side. -/
theorem sin_angle_add_mul_norm_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
Real.sin (angle x (x + y)) * ‖x + y‖ = ‖y‖ := by
by_cases h0 : x = 0 ∧ y = 0; · simp [h0]
rw [not_and_or] at h0
rw [sin_angle_add_of_inner_eq_zero h h0, div_mul_cancel₀]
rw [← mul_self_ne_zero, norm_add_sq_eq_norm_sq_add_norm_sq_real h]
refine (ne_of_lt ?_).symm
rcases h0 with (h0 | h0)
· exact Left.add_pos_of_pos_of_nonneg (mul_self_pos.2 (norm_ne_zero_iff.2 h0)) (mul_self_nonneg _)
· exact Left.add_pos_of_nonneg_of_pos (mul_self_nonneg _) (mul_self_pos.2 (norm_ne_zero_iff.2 h0))
/-- The tangent of an angle in a right-angled triangle multiplied by the adjacent side equals
the opposite side. -/
theorem tan_angle_add_mul_norm_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0 ∨ y = 0) :
Real.tan (angle x (x + y)) * ‖x‖ = ‖y‖ := by
rw [tan_angle_add_of_inner_eq_zero h]
rcases h0 with (h0 | h0) <;> simp [h0]
/-- A side of a right-angled triangle divided by the cosine of the adjacent angle equals the
hypotenuse. -/
theorem norm_div_cos_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0 ∨ y = 0) :
‖x‖ / Real.cos (angle x (x + y)) = ‖x + y‖ := by
rw [cos_angle_add_of_inner_eq_zero h]
rcases h0 with (h0 | h0)
· rw [div_div_eq_mul_div, mul_comm, div_eq_mul_inv, mul_inv_cancel_right₀ (norm_ne_zero_iff.2 h0)]
· simp [h0]
/-- A side of a right-angled triangle divided by the sine of the opposite angle equals the
hypotenuse. -/
theorem norm_div_sin_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x = 0 ∨ y ≠ 0) :
‖y‖ / Real.sin (angle x (x + y)) = ‖x + y‖ := by
rcases h0 with (h0 | h0); · simp [h0]
rw [sin_angle_add_of_inner_eq_zero h (Or.inr h0), div_div_eq_mul_div, mul_comm, div_eq_mul_inv,
mul_inv_cancel_right₀ (norm_ne_zero_iff.2 h0)]
/-- A side of a right-angled triangle divided by the tangent of the opposite angle equals the
adjacent side. -/
theorem norm_div_tan_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x = 0 ∨ y ≠ 0) :
‖y‖ / Real.tan (angle x (x + y)) = ‖x‖ := by
rw [tan_angle_add_of_inner_eq_zero h]
rcases h0 with (h0 | h0)
· simp [h0]
· rw [div_div_eq_mul_div, mul_comm, div_eq_mul_inv, mul_inv_cancel_right₀ (norm_ne_zero_iff.2 h0)]
/-- An angle in a right-angled triangle expressed using `arccos`, version subtracting vectors. -/
theorem angle_sub_eq_arccos_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
angle x (x - y) = Real.arccos (‖x‖ / ‖x - y‖) := by
rw [← neg_eq_zero, ← inner_neg_right] at h
rw [sub_eq_add_neg, angle_add_eq_arccos_of_inner_eq_zero h]
/-- An angle in a right-angled triangle expressed using `arcsin`, version subtracting vectors. -/
theorem angle_sub_eq_arcsin_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0 ∨ y ≠ 0) :
angle x (x - y) = Real.arcsin (‖y‖ / ‖x - y‖) := by
rw [← neg_eq_zero, ← inner_neg_right] at h
rw [or_comm, ← neg_ne_zero, or_comm] at h0
rw [sub_eq_add_neg, angle_add_eq_arcsin_of_inner_eq_zero h h0, norm_neg]
/-- An angle in a right-angled triangle expressed using `arctan`, version subtracting vectors. -/
theorem angle_sub_eq_arctan_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0) :
angle x (x - y) = Real.arctan (‖y‖ / ‖x‖) := by
rw [← neg_eq_zero, ← inner_neg_right] at h
rw [sub_eq_add_neg, angle_add_eq_arctan_of_inner_eq_zero h h0, norm_neg]
/-- An angle in a non-degenerate right-angled triangle is positive, version subtracting
vectors. -/
theorem angle_sub_pos_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x = 0 ∨ y ≠ 0) :
0 < angle x (x - y) := by
rw [← neg_eq_zero, ← inner_neg_right] at h
rw [← neg_ne_zero] at h0
rw [sub_eq_add_neg]
exact angle_add_pos_of_inner_eq_zero h h0
/-- An angle in a right-angled triangle is at most `π / 2`, version subtracting vectors. -/
theorem angle_sub_le_pi_div_two_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
angle x (x - y) ≤ π / 2 := by
rw [← neg_eq_zero, ← inner_neg_right] at h
rw [sub_eq_add_neg]
exact angle_add_le_pi_div_two_of_inner_eq_zero h
/-- An angle in a non-degenerate right-angled triangle is less than `π / 2`, version subtracting
vectors. -/
theorem angle_sub_lt_pi_div_two_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0) :
angle x (x - y) < π / 2 := by
rw [← neg_eq_zero, ← inner_neg_right] at h
rw [sub_eq_add_neg]
exact angle_add_lt_pi_div_two_of_inner_eq_zero h h0
/-- The cosine of an angle in a right-angled triangle as a ratio of sides, version subtracting
vectors. -/
| Mathlib/Geometry/Euclidean/Angle/Unoriented/RightAngle.lean | 248 | 253 | theorem cos_angle_sub_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
Real.cos (angle x (x - y)) = ‖x‖ / ‖x - y‖ := by | rw [← neg_eq_zero, ← inner_neg_right] at h
rw [sub_eq_add_neg, cos_angle_add_of_inner_eq_zero h]
/-- The sine of an angle in a right-angled triangle as a ratio of sides, version subtracting |
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.Calculus.Deriv.Basic
import Mathlib.Analysis.Calculus.ContDiff.Defs
/-!
# One-dimensional iterated derivatives
We define the `n`-th derivative of a function `f : 𝕜 → F` as a function
`iteratedDeriv n f : 𝕜 → F`, as well as a version on domains `iteratedDerivWithin n f s : 𝕜 → F`,
and prove their basic properties.
## Main definitions and results
Let `𝕜` be a nontrivially normed field, and `F` a normed vector space over `𝕜`. Let `f : 𝕜 → F`.
* `iteratedDeriv n f` is the `n`-th derivative of `f`, seen as a function from `𝕜` to `F`.
It is defined as the `n`-th Fréchet derivative (which is a multilinear map) applied to the
vector `(1, ..., 1)`, to take advantage of all the existing framework, but we show that it
coincides with the naive iterative definition.
* `iteratedDeriv_eq_iterate` states that the `n`-th derivative of `f` is obtained by starting
from `f` and differentiating it `n` times.
* `iteratedDerivWithin n f s` is the `n`-th derivative of `f` within the domain `s`. It only
behaves well when `s` has the unique derivative property.
* `iteratedDerivWithin_eq_iterate` states that the `n`-th derivative of `f` in the domain `s` is
obtained by starting from `f` and differentiating it `n` times within `s`. This only holds when
`s` has the unique derivative property.
## Implementation details
The results are deduced from the corresponding results for the more general (multilinear) iterated
Fréchet derivative. For this, we write `iteratedDeriv n f` as the composition of
`iteratedFDeriv 𝕜 n f` and a continuous linear equiv. As continuous linear equivs respect
differentiability and commute with differentiation, this makes it possible to prove readily that
the derivative of the `n`-th derivative is the `n+1`-th derivative in `iteratedDerivWithin_succ`,
by translating the corresponding result `iteratedFDerivWithin_succ_apply_left` for the
iterated Fréchet derivative.
-/
noncomputable section
open scoped Topology
open Filter Asymptotics Set
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜]
variable {F : Type*} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
/-- The `n`-th iterated derivative of a function from `𝕜` to `F`, as a function from `𝕜` to `F`. -/
def iteratedDeriv (n : ℕ) (f : 𝕜 → F) (x : 𝕜) : F :=
(iteratedFDeriv 𝕜 n f x : (Fin n → 𝕜) → F) fun _ : Fin n => 1
/-- The `n`-th iterated derivative of a function from `𝕜` to `F` within a set `s`, as a function
from `𝕜` to `F`. -/
def iteratedDerivWithin (n : ℕ) (f : 𝕜 → F) (s : Set 𝕜) (x : 𝕜) : F :=
(iteratedFDerivWithin 𝕜 n f s x : (Fin n → 𝕜) → F) fun _ : Fin n => 1
variable {n : ℕ} {f : 𝕜 → F} {s : Set 𝕜} {x : 𝕜}
theorem iteratedDerivWithin_univ : iteratedDerivWithin n f univ = iteratedDeriv n f := by
ext x
rw [iteratedDerivWithin, iteratedDeriv, iteratedFDerivWithin_univ]
/-! ### Properties of the iterated derivative within a set -/
theorem iteratedDerivWithin_eq_iteratedFDerivWithin : iteratedDerivWithin n f s x =
(iteratedFDerivWithin 𝕜 n f s x : (Fin n → 𝕜) → F) fun _ : Fin n => 1 :=
rfl
/-- Write the iterated derivative as the composition of a continuous linear equiv and the iterated
Fréchet derivative -/
theorem iteratedDerivWithin_eq_equiv_comp : iteratedDerivWithin n f s =
(ContinuousMultilinearMap.piFieldEquiv 𝕜 (Fin n) F).symm ∘ iteratedFDerivWithin 𝕜 n f s := by
ext x; rfl
/-- Write the iterated Fréchet derivative as the composition of a continuous linear equiv and the
iterated derivative. -/
theorem iteratedFDerivWithin_eq_equiv_comp :
iteratedFDerivWithin 𝕜 n f s =
ContinuousMultilinearMap.piFieldEquiv 𝕜 (Fin n) F ∘ iteratedDerivWithin n f s := by
rw [iteratedDerivWithin_eq_equiv_comp, ← Function.comp_assoc, LinearIsometryEquiv.self_comp_symm,
Function.id_comp]
/-- The `n`-th Fréchet derivative applied to a vector `(m 0, ..., m (n-1))` is the derivative
multiplied by the product of the `m i`s. -/
theorem iteratedFDerivWithin_apply_eq_iteratedDerivWithin_mul_prod {m : Fin n → 𝕜} :
(iteratedFDerivWithin 𝕜 n f s x : (Fin n → 𝕜) → F) m =
(∏ i, m i) • iteratedDerivWithin n f s x := by
rw [iteratedDerivWithin_eq_iteratedFDerivWithin, ← ContinuousMultilinearMap.map_smul_univ]
simp
theorem norm_iteratedFDerivWithin_eq_norm_iteratedDerivWithin :
‖iteratedFDerivWithin 𝕜 n f s x‖ = ‖iteratedDerivWithin n f s x‖ := by
rw [iteratedDerivWithin_eq_equiv_comp, Function.comp_apply, LinearIsometryEquiv.norm_map]
@[simp]
| Mathlib/Analysis/Calculus/IteratedDeriv/Defs.lean | 100 | 104 | theorem iteratedDerivWithin_zero : iteratedDerivWithin 0 f s = f := by | ext x
simp [iteratedDerivWithin]
@[simp] |
/-
Copyright (c) 2022 Michael Stoll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Michael Stoll
-/
import Mathlib.Data.Fintype.Parity
import Mathlib.NumberTheory.LegendreSymbol.ZModChar
import Mathlib.FieldTheory.Finite.Basic
/-!
# Quadratic characters of finite fields
This file defines the quadratic character on a finite field `F` and proves
some basic statements about it.
## Tags
quadratic character
-/
/-!
### Definition of the quadratic character
We define the quadratic character of a finite field `F` with values in ℤ.
-/
section Define
/-- Define the quadratic character with values in ℤ on a monoid with zero `α`.
It takes the value zero at zero; for non-zero argument `a : α`, it is `1`
if `a` is a square, otherwise it is `-1`.
This only deserves the name "character" when it is multiplicative,
e.g., when `α` is a finite field. See `quadraticCharFun_mul`.
We will later define `quadraticChar` to be a multiplicative character
of type `MulChar F ℤ`, when the domain is a finite field `F`.
-/
def quadraticCharFun (α : Type*) [MonoidWithZero α] [DecidableEq α]
[DecidablePred (IsSquare : α → Prop)] (a : α) : ℤ :=
if a = 0 then 0 else if IsSquare a then 1 else -1
end Define
/-!
### Basic properties of the quadratic character
We prove some properties of the quadratic character.
We work with a finite field `F` here.
The interesting case is when the characteristic of `F` is odd.
-/
section quadraticChar
open MulChar
variable {F : Type*} [Field F] [Fintype F] [DecidableEq F]
/-- Some basic API lemmas -/
theorem quadraticCharFun_eq_zero_iff {a : F} : quadraticCharFun F a = 0 ↔ a = 0 := by
simp only [quadraticCharFun]
by_cases ha : a = 0
· simp only [ha, if_true]
· simp only [ha, if_false]
split_ifs <;> simp only [neg_eq_zero, one_ne_zero, not_false_iff]
@[simp]
theorem quadraticCharFun_zero : quadraticCharFun F 0 = 0 := by
simp only [quadraticCharFun, if_true]
@[simp]
theorem quadraticCharFun_one : quadraticCharFun F 1 = 1 := by
simp only [quadraticCharFun, one_ne_zero, IsSquare.one, if_true, if_false]
/-- If `ringChar F = 2`, then `quadraticCharFun F` takes the value `1` on nonzero elements. -/
theorem quadraticCharFun_eq_one_of_char_two (hF : ringChar F = 2) {a : F} (ha : a ≠ 0) :
quadraticCharFun F a = 1 := by
simp only [quadraticCharFun, ha, if_false, ite_eq_left_iff]
exact fun h ↦ (h (FiniteField.isSquare_of_char_two hF a)).elim
/-- If `ringChar F` is odd, then `quadraticCharFun F a` can be computed in
terms of `a ^ (Fintype.card F / 2)`. -/
theorem quadraticCharFun_eq_pow_of_char_ne_two (hF : ringChar F ≠ 2) {a : F} (ha : a ≠ 0) :
quadraticCharFun F a = if a ^ (Fintype.card F / 2) = 1 then 1 else -1 := by
simp only [quadraticCharFun, ha, if_false]
simp_rw [FiniteField.isSquare_iff hF ha]
/-- The quadratic character is multiplicative. -/
theorem quadraticCharFun_mul (a b : F) :
quadraticCharFun F (a * b) = quadraticCharFun F a * quadraticCharFun F b := by
by_cases ha : a = 0
· rw [ha, zero_mul, quadraticCharFun_zero, zero_mul]
-- now `a ≠ 0`
by_cases hb : b = 0
· rw [hb, mul_zero, quadraticCharFun_zero, mul_zero]
-- now `a ≠ 0` and `b ≠ 0`
have hab := mul_ne_zero ha hb
by_cases hF : ringChar F = 2
·-- case `ringChar F = 2`
rw [quadraticCharFun_eq_one_of_char_two hF ha, quadraticCharFun_eq_one_of_char_two hF hb,
quadraticCharFun_eq_one_of_char_two hF hab, mul_one]
· -- case of odd characteristic
rw [quadraticCharFun_eq_pow_of_char_ne_two hF ha, quadraticCharFun_eq_pow_of_char_ne_two hF hb,
quadraticCharFun_eq_pow_of_char_ne_two hF hab, mul_pow]
rcases FiniteField.pow_dichotomy hF hb with hb' | hb'
· simp only [hb', mul_one, if_true]
· have h := Ring.neg_one_ne_one_of_char_ne_two hF
-- `-1 ≠ 1`
simp only [hb', mul_neg, mul_one, h, if_false]
rcases FiniteField.pow_dichotomy hF ha with ha' | ha' <;>
simp only [ha', h, neg_neg, if_true, if_false]
variable (F) in
/-- The quadratic character as a multiplicative character. -/
@[simps]
def quadraticChar : MulChar F ℤ where
toFun := quadraticCharFun F
map_one' := quadraticCharFun_one
map_mul' := quadraticCharFun_mul
map_nonunit' a ha := by rw [of_not_not (mt Ne.isUnit ha)]; exact quadraticCharFun_zero
/-- The value of the quadratic character on `a` is zero iff `a = 0`. -/
theorem quadraticChar_eq_zero_iff {a : F} : quadraticChar F a = 0 ↔ a = 0 :=
quadraticCharFun_eq_zero_iff
theorem quadraticChar_zero : quadraticChar F 0 = 0 := by
simp only [quadraticChar_apply, quadraticCharFun_zero]
/-- For nonzero `a : F`, `quadraticChar F a = 1 ↔ IsSquare a`. -/
theorem quadraticChar_one_iff_isSquare {a : F} (ha : a ≠ 0) :
quadraticChar F a = 1 ↔ IsSquare a := by
simp only [quadraticChar_apply, quadraticCharFun, ha, if_false, ite_eq_left_iff,
(by omega : (-1 : ℤ) ≠ 1), imp_false, not_not, reduceCtorEq]
/-- The quadratic character takes the value `1` on nonzero squares. -/
theorem quadraticChar_sq_one' {a : F} (ha : a ≠ 0) : quadraticChar F (a ^ 2) = 1 := by
simp only [quadraticChar_apply, quadraticCharFun, sq_eq_zero_iff, ha, IsSquare.sq, if_true,
if_false]
/-- The square of the quadratic character on nonzero arguments is `1`. -/
| Mathlib/NumberTheory/LegendreSymbol/QuadraticChar/Basic.lean | 144 | 145 | theorem quadraticChar_sq_one {a : F} (ha : a ≠ 0) : quadraticChar F a ^ 2 = 1 := by | rwa [pow_two, ← map_mul, ← pow_two, quadraticChar_sq_one'] |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Yury Kudryashov
-/
import Mathlib.MeasureTheory.Constructions.BorelSpace.Order
import Mathlib.MeasureTheory.MeasurableSpace.Prod
import Mathlib.MeasureTheory.Measure.Typeclasses.NoAtoms
import Mathlib.Topology.Instances.Real.Lemmas
/-!
# Borel (measurable) spaces ℝ, ℝ≥0, ℝ≥0∞
## Main statements
* `borel_eq_generateFrom_Ixx_rat` (where Ixx is one of {Ioo, Ioi, Iio, Ici, Iic):
the Borel sigma algebra on ℝ is generated by intervals with rational endpoints;
* `isPiSystem_Ixx_rat` (where Ixx is one of {Ioo, Ioi, Iio, Ici, Iic):
intervals with rational endpoints form a pi system on ℝ;
* `measurable_real_toNNReal`, `measurable_coe_nnreal_real`, `measurable_coe_nnreal_ennreal`,
`ENNReal.measurable_ofReal`, `ENNReal.measurable_toReal`:
measurability of various coercions between ℝ, ℝ≥0, and ℝ≥0∞;
* `Measurable.real_toNNReal`, `Measurable.coe_nnreal_real`, `Measurable.coe_nnreal_ennreal`,
`Measurable.ennreal_ofReal`, `Measurable.ennreal_toNNReal`, `Measurable.ennreal_toReal`:
measurability of functions composed with various coercions between ℝ, ℝ≥0, and ℝ≥0∞
(also similar results for a.e.-measurability);
* `Measurable.ennreal*` : measurability of special cases for arithmetic operations on `ℝ≥0∞`.
-/
open Set Filter MeasureTheory MeasurableSpace
open scoped Topology NNReal ENNReal
universe u v w x y
variable {α β γ δ : Type*} {ι : Sort y} {s t u : Set α}
namespace Real
theorem borel_eq_generateFrom_Ioo_rat :
borel ℝ = .generateFrom (⋃ (a : ℚ) (b : ℚ) (_ : a < b), {Ioo (a : ℝ) (b : ℝ)}) :=
isTopologicalBasis_Ioo_rat.borel_eq_generateFrom
theorem borel_eq_generateFrom_Iio_rat : borel ℝ = .generateFrom (⋃ a : ℚ, {Iio (a : ℝ)}) := by
rw [borel_eq_generateFrom_Iio]
refine le_antisymm
(generateFrom_le ?_)
(generateFrom_mono <| iUnion_subset fun q ↦ singleton_subset_iff.mpr <| mem_range_self _)
rintro _ ⟨a, rfl⟩
have : IsLUB (range ((↑) : ℚ → ℝ) ∩ Iio a) a := by
simp [isLUB_iff_le_iff, mem_upperBounds, ← le_iff_forall_rat_lt_imp_le]
rw [← this.biUnion_Iio_eq, ← image_univ, ← image_inter_preimage, univ_inter, biUnion_image]
exact MeasurableSet.biUnion (to_countable _)
fun b _ => GenerateMeasurable.basic (Iio (b : ℝ)) (by simp)
theorem borel_eq_generateFrom_Ioi_rat : borel ℝ = .generateFrom (⋃ a : ℚ, {Ioi (a : ℝ)}) := by
rw [borel_eq_generateFrom_Ioi]
refine le_antisymm
(generateFrom_le ?_)
(generateFrom_mono <| iUnion_subset fun q ↦ singleton_subset_iff.mpr <| mem_range_self _)
rintro _ ⟨a, rfl⟩
have : IsGLB (range ((↑) : ℚ → ℝ) ∩ Ioi a) a := by
simp [isGLB_iff_le_iff, mem_lowerBounds, ← le_iff_forall_lt_rat_imp_le]
rw [← this.biUnion_Ioi_eq, ← image_univ, ← image_inter_preimage, univ_inter, biUnion_image]
exact MeasurableSet.biUnion (to_countable _)
fun b _ => GenerateMeasurable.basic (Ioi (b : ℝ)) (by simp)
| Mathlib/MeasureTheory/Constructions/BorelSpace/Real.lean | 68 | 74 | theorem borel_eq_generateFrom_Iic_rat : borel ℝ = .generateFrom (⋃ a : ℚ, {Iic (a : ℝ)}) := by | rw [borel_eq_generateFrom_Ioi_rat, iUnion_singleton_eq_range, iUnion_singleton_eq_range]
refine le_antisymm (generateFrom_le ?_) (generateFrom_le ?_) <;>
rintro _ ⟨q, rfl⟩ <;>
dsimp only <;>
[rw [← compl_Iic]; rw [← compl_Ioi]] <;>
exact MeasurableSet.compl (GenerateMeasurable.basic _ (mem_range_self q)) |
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Order.Interval.Set.OrdConnected
import Mathlib.Data.Set.Lattice.Image
/-!
# Order connected components of a set
In this file we define `Set.ordConnectedComponent s x` to be the set of `y` such that
`Set.uIcc x y ⊆ s` and prove some basic facts about this definition. At the moment of writing,
this construction is used only to prove that any linear order with order topology is a T₅ space,
so we only add API needed for this lemma.
-/
open Interval Function OrderDual
namespace Set
variable {α : Type*} [LinearOrder α] {s t : Set α} {x y z : α}
/-- Order-connected component of a point `x` in a set `s`. It is defined as the set of `y` such that
`Set.uIcc x y ⊆ s`. Note that it is empty if and only if `x ∉ s`. -/
def ordConnectedComponent (s : Set α) (x : α) : Set α :=
{ y | [[x, y]] ⊆ s }
theorem mem_ordConnectedComponent : y ∈ ordConnectedComponent s x ↔ [[x, y]] ⊆ s :=
Iff.rfl
theorem dual_ordConnectedComponent :
ordConnectedComponent (ofDual ⁻¹' s) (toDual x) = ofDual ⁻¹' ordConnectedComponent s x :=
ext <| (Surjective.forall toDual.surjective).2 fun x => by simp [mem_ordConnectedComponent]
theorem ordConnectedComponent_subset : ordConnectedComponent s x ⊆ s := fun _ hy =>
hy right_mem_uIcc
theorem subset_ordConnectedComponent {t} [h : OrdConnected s] (hs : x ∈ s) (ht : s ⊆ t) :
s ⊆ ordConnectedComponent t x := fun _ hy => (h.uIcc_subset hs hy).trans ht
@[simp]
theorem self_mem_ordConnectedComponent : x ∈ ordConnectedComponent s x ↔ x ∈ s := by
rw [mem_ordConnectedComponent, uIcc_self, singleton_subset_iff]
@[simp]
theorem nonempty_ordConnectedComponent : (ordConnectedComponent s x).Nonempty ↔ x ∈ s :=
⟨fun ⟨_, hy⟩ => hy <| left_mem_uIcc, fun h => ⟨x, self_mem_ordConnectedComponent.2 h⟩⟩
@[simp]
theorem ordConnectedComponent_eq_empty : ordConnectedComponent s x = ∅ ↔ x ∉ s := by
rw [← not_nonempty_iff_eq_empty, nonempty_ordConnectedComponent]
@[simp]
theorem ordConnectedComponent_empty : ordConnectedComponent ∅ x = ∅ :=
ordConnectedComponent_eq_empty.2 (not_mem_empty x)
@[simp]
theorem ordConnectedComponent_univ : ordConnectedComponent univ x = univ := by
simp [ordConnectedComponent]
theorem ordConnectedComponent_inter (s t : Set α) (x : α) :
ordConnectedComponent (s ∩ t) x = ordConnectedComponent s x ∩ ordConnectedComponent t x := by
simp [ordConnectedComponent, setOf_and]
theorem mem_ordConnectedComponent_comm :
y ∈ ordConnectedComponent s x ↔ x ∈ ordConnectedComponent s y := by
rw [mem_ordConnectedComponent, mem_ordConnectedComponent, uIcc_comm]
theorem mem_ordConnectedComponent_trans (hxy : y ∈ ordConnectedComponent s x)
(hyz : z ∈ ordConnectedComponent s y) : z ∈ ordConnectedComponent s x :=
calc
[[x, z]] ⊆ [[x, y]] ∪ [[y, z]] := uIcc_subset_uIcc_union_uIcc
_ ⊆ s := union_subset hxy hyz
theorem ordConnectedComponent_eq (h : [[x, y]] ⊆ s) :
ordConnectedComponent s x = ordConnectedComponent s y :=
ext fun _ =>
⟨mem_ordConnectedComponent_trans (mem_ordConnectedComponent_comm.2 h),
mem_ordConnectedComponent_trans h⟩
instance : OrdConnected (ordConnectedComponent s x) :=
ordConnected_of_uIcc_subset_left fun _ hy _ hz => (uIcc_subset_uIcc_left hz).trans hy
/-- Projection from `s : Set α` to `α` sending each order connected component of `s` to a single
point of this component. -/
noncomputable def ordConnectedProj (s : Set α) : s → α := fun x : s =>
(nonempty_ordConnectedComponent.2 x.2).some
theorem ordConnectedProj_mem_ordConnectedComponent (s : Set α) (x : s) :
ordConnectedProj s x ∈ ordConnectedComponent s x :=
Nonempty.some_mem _
theorem mem_ordConnectedComponent_ordConnectedProj (s : Set α) (x : s) :
↑x ∈ ordConnectedComponent s (ordConnectedProj s x) :=
mem_ordConnectedComponent_comm.2 <| ordConnectedProj_mem_ordConnectedComponent s x
@[simp]
theorem ordConnectedComponent_ordConnectedProj (s : Set α) (x : s) :
ordConnectedComponent s (ordConnectedProj s x) = ordConnectedComponent s x :=
ordConnectedComponent_eq <| mem_ordConnectedComponent_ordConnectedProj _ _
@[simp]
theorem ordConnectedProj_eq {x y : s} :
ordConnectedProj s x = ordConnectedProj s y ↔ [[(x : α), y]] ⊆ s := by
constructor <;> intro h
· rw [← mem_ordConnectedComponent, ← ordConnectedComponent_ordConnectedProj, h,
ordConnectedComponent_ordConnectedProj, self_mem_ordConnectedComponent]
exact y.2
· simp only [ordConnectedProj, ordConnectedComponent_eq h]
/-- A set that intersects each order connected component of a set by a single point. Defined as the
range of `Set.ordConnectedProj s`. -/
def ordConnectedSection (s : Set α) : Set α :=
range <| ordConnectedProj s
theorem dual_ordConnectedSection (s : Set α) :
ordConnectedSection (ofDual ⁻¹' s) = ofDual ⁻¹' ordConnectedSection s := by
simp only [ordConnectedSection]
simp +unfoldPartialApp only [ordConnectedProj]
ext x
simp only [mem_range, Subtype.exists, mem_preimage, OrderDual.exists, dual_ordConnectedComponent,
ofDual_toDual]
tauto
| Mathlib/Order/Interval/Set/OrdConnectedComponent.lean | 127 | 133 | theorem ordConnectedSection_subset : ordConnectedSection s ⊆ s :=
range_subset_iff.2 fun _ => ordConnectedComponent_subset <| Nonempty.some_mem _
theorem eq_of_mem_ordConnectedSection_of_uIcc_subset (hx : x ∈ ordConnectedSection s)
(hy : y ∈ ordConnectedSection s) (h : [[x, y]] ⊆ s) : x = y := by | rcases hx with ⟨x, rfl⟩; rcases hy with ⟨y, rfl⟩
exact |
/-
Copyright (c) 2024 David Loeffler. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Loeffler
-/
import Mathlib.NumberTheory.ZetaValues
import Mathlib.NumberTheory.LSeries.RiemannZeta
/-!
# Special values of Hurwitz and Riemann zeta functions
This file gives the formula for `ζ (2 * k)`, for `k` a non-zero integer, in terms of Bernoulli
numbers. More generally, we give formulae for any Hurwitz zeta functions at any (strictly) negative
integer in terms of Bernoulli polynomials.
(Note that most of the actual work for these formulae is done elsewhere, in
`Mathlib.NumberTheory.ZetaValues`. This file has only those results which really need the
definition of Hurwitz zeta and related functions, rather than working directly with the defining
sums in the convergence range.)
## Main results
- `hurwitzZeta_neg_nat`: for `k : ℕ` with `k ≠ 0`, and any `x ∈ ℝ / ℤ`, the special value
`hurwitzZeta x (-k)` is equal to `-(Polynomial.bernoulli (k + 1) x) / (k + 1)`.
- `riemannZeta_neg_nat_eq_bernoulli` : for any `k ∈ ℕ` we have the formula
`riemannZeta (-k) = (-1) ^ k * bernoulli (k + 1) / (k + 1)`
- `riemannZeta_two_mul_nat`: formula for `ζ(2 * k)` for `k ∈ ℕ, k ≠ 0` in terms of Bernoulli
numbers
## TODO
* Extend to cover Dirichlet L-functions.
* The formulae are correct for `s = 0` as well, but we do not prove this case, since this requires
Fourier series which are only conditionally convergent, which is difficult to approach using the
methods in the library at the present time (May 2024).
-/
open Complex Real Set
open scoped Nat
namespace HurwitzZeta
variable {k : ℕ} {x : ℝ}
/-- Express the value of `cosZeta` at a positive even integer as a value
of the Bernoulli polynomial. -/
theorem cosZeta_two_mul_nat (hk : k ≠ 0) (hx : x ∈ Icc 0 1) :
cosZeta x (2 * k) = (-1) ^ (k + 1) * (2 * π) ^ (2 * k) / 2 / (2 * k)! *
((Polynomial.bernoulli (2 * k)).map (algebraMap ℚ ℂ)).eval (x : ℂ) := by
rw [← (hasSum_nat_cosZeta x (?_ : 1 < re (2 * k))).tsum_eq]
· refine Eq.trans ?_ <|
(congr_arg ofReal (hasSum_one_div_nat_pow_mul_cos hk hx).tsum_eq).trans ?_
· rw [ofReal_tsum]
refine tsum_congr fun n ↦ ?_
norm_cast
ring_nf
· push_cast
congr 1
have : (Polynomial.bernoulli (2 * k)).map (algebraMap ℚ ℂ) = _ :=
(Polynomial.map_map (algebraMap ℚ ℝ) ofRealHom _).symm
rw [this, ← ofRealHom_eq_coe, ← ofRealHom_eq_coe]
apply Polynomial.map_aeval_eq_aeval_map (by simp)
· norm_cast
omega
/--
Express the value of `sinZeta` at an odd integer `> 1` as a value of the Bernoulli polynomial.
Note that this formula is also correct for `k = 0` (i.e. for the value at `s = 1`), but we do not
prove it in this case, owing to the additional difficulty of working with series that are only
conditionally convergent.
-/
theorem sinZeta_two_mul_nat_add_one (hk : k ≠ 0) (hx : x ∈ Icc 0 1) :
sinZeta x (2 * k + 1) = (-1) ^ (k + 1) * (2 * π) ^ (2 * k + 1) / 2 / (2 * k + 1)! *
((Polynomial.bernoulli (2 * k + 1)).map (algebraMap ℚ ℂ)).eval (x : ℂ) := by
rw [← (hasSum_nat_sinZeta x (?_ : 1 < re (2 * k + 1))).tsum_eq]
· refine Eq.trans ?_ <|
(congr_arg ofReal (hasSum_one_div_nat_pow_mul_sin hk hx).tsum_eq).trans ?_
· rw [ofReal_tsum]
refine tsum_congr fun n ↦ ?_
norm_cast
ring_nf
· push_cast
congr 1
have : (Polynomial.bernoulli (2 * k + 1)).map (algebraMap ℚ ℂ) = _ :=
(Polynomial.map_map (algebraMap ℚ ℝ) ofRealHom _).symm
rw [this, ← ofRealHom_eq_coe, ← ofRealHom_eq_coe]
apply Polynomial.map_aeval_eq_aeval_map (by simp)
· norm_cast
omega
/-- Reformulation of `cosZeta_two_mul_nat` using `Gammaℂ`. -/
theorem cosZeta_two_mul_nat' (hk : k ≠ 0) (hx : x ∈ Icc (0 : ℝ) 1) :
cosZeta x (2 * k) = (-1) ^ (k + 1) / (2 * k) / Gammaℂ (2 * k) *
((Polynomial.bernoulli (2 * k)).map (algebraMap ℚ ℂ)).eval (x : ℂ) := by
rw [cosZeta_two_mul_nat hk hx]
congr 1
have : (2 * k)! = (2 * k) * Complex.Gamma (2 * k) := by
rw [(by { norm_cast; omega } : 2 * (k : ℂ) = ↑(2 * k - 1) + 1), Complex.Gamma_nat_eq_factorial,
← Nat.cast_add_one, ← Nat.cast_mul, ← Nat.factorial_succ, Nat.sub_add_cancel (by omega)]
simp_rw [this, Gammaℂ, cpow_neg, ← div_div, div_inv_eq_mul, div_mul_eq_mul_div, div_div,
mul_right_comm (2 : ℂ) (k : ℂ)]
norm_cast
/-- Reformulation of `sinZeta_two_mul_nat_add_one` using `Gammaℂ`. -/
theorem sinZeta_two_mul_nat_add_one' (hk : k ≠ 0) (hx : x ∈ Icc (0 : ℝ) 1) :
sinZeta x (2 * k + 1) = (-1) ^ (k + 1) / (2 * k + 1) / Gammaℂ (2 * k + 1) *
((Polynomial.bernoulli (2 * k + 1)).map (algebraMap ℚ ℂ)).eval (x : ℂ) := by
rw [sinZeta_two_mul_nat_add_one hk hx]
congr 1
have : (2 * k + 1)! = (2 * k + 1) * Complex.Gamma (2 * k + 1) := by
rw [(by simp : Complex.Gamma (2 * k + 1) = Complex.Gamma (↑(2 * k) + 1)),
Complex.Gamma_nat_eq_factorial, ← Nat.cast_ofNat (R := ℂ), ← Nat.cast_mul,
← Nat.cast_add_one, ← Nat.cast_mul, ← Nat.factorial_succ]
simp_rw [this, Gammaℂ, cpow_neg, ← div_div, div_inv_eq_mul, div_mul_eq_mul_div, div_div]
rw [(by simp : 2 * (k : ℂ) + 1 = ↑(2 * k + 1)), cpow_natCast]
ring
theorem hurwitzZetaEven_one_sub_two_mul_nat (hk : k ≠ 0) (hx : x ∈ Icc (0 : ℝ) 1) :
hurwitzZetaEven x (1 - 2 * k) =
-1 / (2 * k) * ((Polynomial.bernoulli (2 * k)).map (algebraMap ℚ ℂ)).eval (x : ℂ) := by
have h1 (n : ℕ) : (2 * k : ℂ) ≠ -n := by
rw [← Int.cast_ofNat, ← Int.cast_natCast, ← Int.cast_mul, ← Int.cast_natCast n, ← Int.cast_neg,
Ne, Int.cast_inj, ← Ne]
refine ne_of_gt ((neg_nonpos_of_nonneg n.cast_nonneg).trans_lt (mul_pos two_pos ?_))
exact Nat.cast_pos.mpr (Nat.pos_of_ne_zero hk)
have h2 : (2 * k : ℂ) ≠ 1 := by norm_cast; simp
have h3 : Gammaℂ (2 * k) ≠ 0 := by
refine mul_ne_zero (mul_ne_zero two_ne_zero ?_) (Gamma_ne_zero h1)
simp [pi_ne_zero]
rw [hurwitzZetaEven_one_sub _ h1 (Or.inr h2), ← Gammaℂ, cosZeta_two_mul_nat' hk hx, ← mul_assoc,
← mul_div_assoc, mul_assoc, mul_div_cancel_left₀ _ h3, ← mul_div_assoc]
congr 2
rw [mul_div_assoc, mul_div_cancel_left₀ _ two_ne_zero, ← ofReal_natCast, ← ofReal_mul,
← ofReal_cos, mul_comm π, ← sub_zero (k * π), cos_nat_mul_pi_sub, Real.cos_zero, mul_one,
ofReal_pow, ofReal_neg, ofReal_one, pow_succ, mul_neg_one, mul_neg, ← mul_pow, neg_one_mul,
neg_neg, one_pow]
theorem hurwitzZetaOdd_neg_two_mul_nat (hk : k ≠ 0) (hx : x ∈ Icc (0 : ℝ) 1) :
hurwitzZetaOdd x (-(2 * k)) =
-1 / (2 * k + 1) * ((Polynomial.bernoulli (2 * k + 1)).map (algebraMap ℚ ℂ)).eval (x : ℂ) := by
have h1 (n : ℕ) : (2 * k + 1 : ℂ) ≠ -n := by
rw [← Int.cast_ofNat, ← Int.cast_natCast, ← Int.cast_mul, ← Int.cast_natCast n, ← Int.cast_neg,
← Int.cast_one, ← Int.cast_add, Ne, Int.cast_inj, ← Ne]
refine ne_of_gt ((neg_nonpos_of_nonneg n.cast_nonneg).trans_lt ?_)
positivity
have h3 : Gammaℂ (2 * k + 1) ≠ 0 := by
refine mul_ne_zero (mul_ne_zero two_ne_zero ?_) (Gamma_ne_zero h1)
simp [pi_ne_zero]
rw [(by simp : -(2 * k : ℂ) = 1 - (2 * k + 1)),
hurwitzZetaOdd_one_sub _ h1, ← Gammaℂ, sinZeta_two_mul_nat_add_one' hk hx, ← mul_assoc,
← mul_div_assoc, mul_assoc, mul_div_cancel_left₀ _ h3, ← mul_div_assoc]
congr 2
rw [mul_div_assoc, add_div, mul_div_cancel_left₀ _ two_ne_zero, ← ofReal_natCast,
← ofReal_one, ← ofReal_ofNat, ← ofReal_div, ← ofReal_add, ← ofReal_mul,
← ofReal_sin, mul_comm π, add_mul, mul_comm (1 / 2), mul_one_div, Real.sin_add_pi_div_two,
← sub_zero (k * π), cos_nat_mul_pi_sub, Real.cos_zero, mul_one,
ofReal_pow, ofReal_neg, ofReal_one, pow_succ, mul_neg_one, mul_neg, ← mul_pow, neg_one_mul,
neg_neg, one_pow]
-- private because it is superseded by `hurwitzZeta_neg_nat` below
private lemma hurwitzZeta_one_sub_two_mul_nat (hk : k ≠ 0) (hx : x ∈ Icc (0 : ℝ) 1) :
hurwitzZeta x (1 - 2 * k) =
-1 / (2 * k) * ((Polynomial.bernoulli (2 * k)).map (algebraMap ℚ ℂ)).eval (x : ℂ) := by
suffices hurwitzZetaOdd x (1 - 2 * k) = 0 by
rw [hurwitzZeta, this, add_zero, hurwitzZetaEven_one_sub_two_mul_nat hk hx]
obtain ⟨k, rfl⟩ := Nat.exists_eq_succ_of_ne_zero hk
rw [Nat.cast_succ, show (1 : ℂ) - 2 * (k + 1) = -2 * k - 1 by ring,
hurwitzZetaOdd_neg_two_mul_nat_sub_one]
-- private because it is superseded by `hurwitzZeta_neg_nat` below
private lemma hurwitzZeta_neg_two_mul_nat (hk : k ≠ 0) (hx : x ∈ Icc (0 : ℝ) 1) :
hurwitzZeta x (-(2 * k)) = -1 / (2 * k + 1) *
((Polynomial.bernoulli (2 * k + 1)).map (algebraMap ℚ ℂ)).eval (x : ℂ) := by
suffices hurwitzZetaEven x (-(2 * k)) = 0 by
rw [hurwitzZeta, this, zero_add, hurwitzZetaOdd_neg_two_mul_nat hk hx]
obtain ⟨k, rfl⟩ := Nat.exists_eq_succ_of_ne_zero hk
simpa using hurwitzZetaEven_neg_two_mul_nat_add_one x k
/-- Values of Hurwitz zeta functions at (strictly) negative integers.
TODO: This formula is also correct for `k = 0`; but our current proof does not work in this
case. -/
theorem hurwitzZeta_neg_nat (hk : k ≠ 0) (hx : x ∈ Icc (0 : ℝ) 1) :
hurwitzZeta x (-k) =
-1 / (k + 1) * ((Polynomial.bernoulli (k + 1)).map (algebraMap ℚ ℂ)).eval (x : ℂ) := by
rcases Nat.even_or_odd' k with ⟨n, (rfl | rfl)⟩
· exact_mod_cast hurwitzZeta_neg_two_mul_nat (by omega : n ≠ 0) hx
· exact_mod_cast hurwitzZeta_one_sub_two_mul_nat (by omega : n + 1 ≠ 0) hx
end HurwitzZeta
open HurwitzZeta
/-- Explicit formula for `ζ (2 * k)`, for `k ∈ ℕ` with `k ≠ 0`, in terms of the Bernoulli number
`bernoulli (2 * k)`.
Compare `hasSum_zeta_nat` for a version formulated in terms of a sum over `1 / n ^ (2 * k)`, and
`riemannZeta_neg_nat_eq_bernoulli` for values at negative integers (equivalent to the above via
the functional equation). -/
theorem riemannZeta_two_mul_nat {k : ℕ} (hk : k ≠ 0) :
riemannZeta (2 * k) = (-1) ^ (k + 1) * (2 : ℂ) ^ (2 * k - 1)
* (π : ℂ) ^ (2 * k) * bernoulli (2 * k) / (2 * k)! := by
convert congr_arg ((↑) : ℝ → ℂ) (hasSum_zeta_nat hk).tsum_eq
· rw [← Nat.cast_two, ← Nat.cast_mul, zeta_nat_eq_tsum_of_gt_one (by omega)]
simp [push_cast]
· norm_cast
| Mathlib/NumberTheory/LSeries/HurwitzZetaValues.lean | 211 | 217 | theorem riemannZeta_two : riemannZeta 2 = (π : ℂ) ^ 2 / 6 := by | convert congr_arg ((↑) : ℝ → ℂ) hasSum_zeta_two.tsum_eq
· rw [← Nat.cast_two, zeta_nat_eq_tsum_of_gt_one one_lt_two]
simp [push_cast]
· norm_cast
theorem riemannZeta_four : riemannZeta 4 = π ^ 4 / 90 := by |
/-
Copyright (c) 2023 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Algebra.Notation.Pi
import Mathlib.Algebra.Order.Monoid.Defs
import Mathlib.Algebra.Order.Monoid.Unbundled.ExistsOfLE
import Mathlib.Data.Finset.Lattice.Fold
import Mathlib.Data.Fintype.Basic
/-!
# Lemmas about (finite domain) functions into fields.
We split this from `Algebra.Order.Field.Basic` to avoid importing the finiteness hierarchy there.
-/
variable {α ι : Type*} [AddCommMonoid α] [LinearOrder α] [IsOrderedCancelAddMonoid α]
[Nontrivial α] [DenselyOrdered α]
| Mathlib/Algebra/Order/Field/Pi.lean | 21 | 31 | theorem Pi.exists_forall_pos_add_lt [ExistsAddOfLE α] [Finite ι] {x y : ι → α}
(h : ∀ i, x i < y i) : ∃ ε, 0 < ε ∧ ∀ i, x i + ε < y i := by | cases nonempty_fintype ι
cases isEmpty_or_nonempty ι
· obtain ⟨a, ha⟩ := exists_ne (0 : α)
obtain ha | ha := ha.lt_or_lt <;> obtain ⟨b, hb, -⟩ := exists_pos_add_of_lt' ha <;>
exact ⟨b, hb, isEmptyElim⟩
choose ε hε hxε using fun i => exists_pos_add_of_lt' (h i)
obtain rfl : x + ε = y := funext hxε
have hε : 0 < Finset.univ.inf' Finset.univ_nonempty ε := (Finset.lt_inf'_iff _).2 fun i _ => hε _
obtain ⟨δ, hδ, hδε⟩ := exists_between hε |
/-
Copyright (c) 2021 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth
-/
import Mathlib.Analysis.Calculus.Deriv.Inv
import Mathlib.Analysis.Complex.Circle
import Mathlib.Analysis.NormedSpace.BallAction
import Mathlib.Analysis.SpecialFunctions.ExpDeriv
import Mathlib.Analysis.InnerProductSpace.Calculus
import Mathlib.Analysis.InnerProductSpace.PiL2
import Mathlib.Data.Complex.FiniteDimensional
import Mathlib.Geometry.Manifold.Algebra.LieGroup
import Mathlib.Geometry.Manifold.Instances.Real
import Mathlib.Geometry.Manifold.MFDeriv.Basic
import Mathlib.Tactic.Module
/-!
# Manifold structure on the sphere
This file defines stereographic projection from the sphere in an inner product space `E`, and uses
it to put an analytic manifold structure on the sphere.
## Main results
For a unit vector `v` in `E`, the definition `stereographic` gives the stereographic projection
centred at `v`, a partial homeomorphism from the sphere to `(ℝ ∙ v)ᗮ` (the orthogonal complement of
`v`).
For finite-dimensional `E`, we then construct an analytic manifold instance on the sphere; the
charts here are obtained by composing the partial homeomorphisms `stereographic` with arbitrary
isometries from `(ℝ ∙ v)ᗮ` to Euclidean space.
We prove two lemmas about `C^n` maps:
* `contMDiff_coe_sphere` states that the coercion map from the sphere into `E` is analytic;
this is a useful tool for constructing smooth maps *from* the sphere.
* `contMDiff.codRestrict_sphere` states that a map from a manifold into the sphere is
`C^m` if its lift to a map to `E` is `C^m`; this is a useful tool for constructing `C^m` maps
*to* the sphere.
As an application we prove `contMDiffNegSphere`, that the antipodal map is analytic.
Finally, we equip the `Circle` (defined in `Analysis.Complex.Circle` to be the sphere in `ℂ`
centred at `0` of radius `1`) with the following structure:
* a charted space with model space `EuclideanSpace ℝ (Fin 1)` (inherited from `Metric.Sphere`)
* an analytic Lie group with model with corners `𝓡 1`
We furthermore show that `Circle.exp` (defined in `Analysis.Complex.Circle` to be the natural
map `fun t ↦ exp (t * I)` from `ℝ` to `Circle`) is analytic.
## Implementation notes
The model space for the charted space instance is `EuclideanSpace ℝ (Fin n)`, where `n` is a
natural number satisfying the typeclass assumption `[Fact (finrank ℝ E = n + 1)]`. This may seem a
little awkward, but it is designed to circumvent the problem that the literal expression for the
dimension of the model space (up to definitional equality) determines the type. If one used the
naive expression `EuclideanSpace ℝ (Fin (finrank ℝ E - 1))` for the model space, then the sphere in
`ℂ` would be a manifold with model space `EuclideanSpace ℝ (Fin (2 - 1))` but not with model space
`EuclideanSpace ℝ (Fin 1)`.
## TODO
Relate the stereographic projection to the inversion of the space.
-/
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
noncomputable section
open Metric Module Function
open scoped Manifold ContDiff
section StereographicProjection
variable (v : E)
/-! ### Construction of the stereographic projection -/
/-- Stereographic projection, forward direction. This is a map from an inner product space `E` to
the orthogonal complement of an element `v` of `E`. It is smooth away from the affine hyperplane
through `v` parallel to the orthogonal complement. It restricts on the sphere to the stereographic
projection. -/
def stereoToFun (x : E) : (ℝ ∙ v)ᗮ :=
(2 / ((1 : ℝ) - innerSL ℝ v x)) • (ℝ ∙ v)ᗮ.orthogonalProjection x
variable {v}
@[simp]
theorem stereoToFun_apply (x : E) :
stereoToFun v x = (2 / ((1 : ℝ) - innerSL ℝ v x)) • (ℝ ∙ v)ᗮ.orthogonalProjection x :=
rfl
theorem contDiffOn_stereoToFun {n : WithTop ℕ∞} :
ContDiffOn ℝ n (stereoToFun v) {x : E | innerSL _ v x ≠ (1 : ℝ)} := by
refine ContDiffOn.smul ?_ (ℝ ∙ v)ᗮ.orthogonalProjection.contDiff.contDiffOn
refine contDiff_const.contDiffOn.div ?_ ?_
· exact (contDiff_const.sub (innerSL ℝ v).contDiff).contDiffOn
· intro x h h'
exact h (sub_eq_zero.mp h').symm
theorem continuousOn_stereoToFun :
ContinuousOn (stereoToFun v) {x : E | innerSL _ v x ≠ (1 : ℝ)} :=
(contDiffOn_stereoToFun (n := 0)).continuousOn
variable (v) in
/-- Auxiliary function for the construction of the reverse direction of the stereographic
projection. This is a map from the orthogonal complement of a unit vector `v` in an inner product
space `E` to `E`; we will later prove that it takes values in the unit sphere.
For most purposes, use `stereoInvFun`, not `stereoInvFunAux`. -/
def stereoInvFunAux (w : E) : E :=
(‖w‖ ^ 2 + 4)⁻¹ • ((4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v)
@[simp]
theorem stereoInvFunAux_apply (w : E) :
stereoInvFunAux v w = (‖w‖ ^ 2 + 4)⁻¹ • ((4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v) :=
rfl
theorem stereoInvFunAux_mem (hv : ‖v‖ = 1) {w : E} (hw : w ∈ (ℝ ∙ v)ᗮ) :
stereoInvFunAux v w ∈ sphere (0 : E) 1 := by
have h₁ : (0 : ℝ) < ‖w‖ ^ 2 + 4 := by positivity
suffices ‖(4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v‖ = ‖w‖ ^ 2 + 4 by
simp only [mem_sphere_zero_iff_norm, norm_smul, Real.norm_eq_abs, abs_inv, this,
abs_of_pos h₁, stereoInvFunAux_apply, inv_mul_cancel₀ h₁.ne']
suffices ‖(4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v‖ ^ 2 = (‖w‖ ^ 2 + 4) ^ 2 by
simpa only [sq_eq_sq_iff_abs_eq_abs, abs_norm, abs_of_pos h₁] using this
rw [Submodule.mem_orthogonal_singleton_iff_inner_left] at hw
simp [norm_add_sq_real, norm_smul, inner_smul_left, inner_smul_right, hw, mul_pow,
Real.norm_eq_abs, hv]
ring
theorem hasFDerivAt_stereoInvFunAux (v : E) :
HasFDerivAt (stereoInvFunAux v) (ContinuousLinearMap.id ℝ E) 0 := by
have h₀ : HasFDerivAt (fun w : E => ‖w‖ ^ 2) (0 : E →L[ℝ] ℝ) 0 := by
convert (hasStrictFDerivAt_norm_sq (0 : E)).hasFDerivAt
simp only [map_zero, smul_zero]
have h₁ : HasFDerivAt (fun w : E => (‖w‖ ^ 2 + 4)⁻¹) (0 : E →L[ℝ] ℝ) 0 := by
convert (hasFDerivAt_inv _).comp _ (h₀.add (hasFDerivAt_const 4 0)) <;> simp
have h₂ : HasFDerivAt (fun w => (4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v)
((4 : ℝ) • ContinuousLinearMap.id ℝ E) 0 := by
convert ((hasFDerivAt_const (4 : ℝ) 0).smul (hasFDerivAt_id 0)).add
((h₀.sub (hasFDerivAt_const (4 : ℝ) 0)).smul (hasFDerivAt_const v 0)) using 1
ext w
simp
convert h₁.smul h₂ using 1
ext w
simp
theorem hasFDerivAt_stereoInvFunAux_comp_coe (v : E) :
HasFDerivAt (stereoInvFunAux v ∘ ((↑) : (ℝ ∙ v)ᗮ → E)) (ℝ ∙ v)ᗮ.subtypeL 0 := by
have : HasFDerivAt (stereoInvFunAux v) (ContinuousLinearMap.id ℝ E) ((ℝ ∙ v)ᗮ.subtypeL 0) :=
hasFDerivAt_stereoInvFunAux v
refine this.comp (0 : (ℝ ∙ v)ᗮ) (by apply ContinuousLinearMap.hasFDerivAt)
theorem contDiff_stereoInvFunAux {m : WithTop ℕ∞} : ContDiff ℝ m (stereoInvFunAux v) := by
have h₀ : ContDiff ℝ ω fun w : E => ‖w‖ ^ 2 := contDiff_norm_sq ℝ
have h₁ : ContDiff ℝ ω fun w : E => (‖w‖ ^ 2 + 4)⁻¹ := by
refine (h₀.add contDiff_const).inv ?_
intro x
nlinarith
have h₂ : ContDiff ℝ ω fun w => (4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v := by
refine (contDiff_const.smul contDiff_id).add ?_
exact (h₀.sub contDiff_const).smul contDiff_const
exact (h₁.smul h₂).of_le le_top
/-- Stereographic projection, reverse direction. This is a map from the orthogonal complement of a
unit vector `v` in an inner product space `E` to the unit sphere in `E`. -/
def stereoInvFun (hv : ‖v‖ = 1) (w : (ℝ ∙ v)ᗮ) : sphere (0 : E) 1 :=
⟨stereoInvFunAux v (w : E), stereoInvFunAux_mem hv w.2⟩
@[simp]
theorem stereoInvFun_apply (hv : ‖v‖ = 1) (w : (ℝ ∙ v)ᗮ) :
(stereoInvFun hv w : E) = (‖w‖ ^ 2 + 4)⁻¹ • ((4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v) :=
rfl
open scoped InnerProductSpace in
theorem stereoInvFun_ne_north_pole (hv : ‖v‖ = 1) (w : (ℝ ∙ v)ᗮ) :
stereoInvFun hv w ≠ (⟨v, by simp [hv]⟩ : sphere (0 : E) 1) := by
refine Subtype.coe_ne_coe.1 ?_
rw [← inner_lt_one_iff_real_of_norm_one _ hv]
· have hw : ⟪v, w⟫_ℝ = 0 := Submodule.mem_orthogonal_singleton_iff_inner_right.mp w.2
have hw' : (‖(w : E)‖ ^ 2 + 4)⁻¹ * (‖(w : E)‖ ^ 2 - 4) < 1 := by
rw [inv_mul_lt_iff₀']
· linarith
positivity
simpa [real_inner_comm, inner_add_right, inner_smul_right, real_inner_self_eq_norm_mul_norm, hw,
hv] using hw'
· simpa using stereoInvFunAux_mem hv w.2
| Mathlib/Geometry/Manifold/Instances/Sphere.lean | 194 | 205 | theorem continuous_stereoInvFun (hv : ‖v‖ = 1) : Continuous (stereoInvFun hv) :=
continuous_induced_rng.2
((contDiff_stereoInvFunAux (m := 0)).continuous.comp continuous_subtype_val)
open scoped InnerProductSpace in
attribute [-simp] AddSubgroupClass.coe_norm Submodule.coe_norm in
theorem stereo_left_inv (hv : ‖v‖ = 1) {x : sphere (0 : E) 1} (hx : (x : E) ≠ v) :
stereoInvFun hv (stereoToFun v x) = x := by | ext
simp only [stereoToFun_apply, stereoInvFun_apply, smul_add]
-- name two frequently-occurring quantities and write down their basic properties
set a : ℝ := innerSL _ v x |
/-
Copyright (c) 2023 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Dynamics.BirkhoffSum.Basic
import Mathlib.Algebra.Module.Basic
/-!
# Birkhoff average
In this file we define `birkhoffAverage f g n x` to be
$$
\frac{1}{n}\sum_{k=0}^{n-1}g(f^{[k]}(x)),
$$
where `f : α → α` is a self-map on some type `α`,
`g : α → M` is a function from `α` to a module over a division semiring `R`,
and `R` is used to formalize division by `n` as `(n : R)⁻¹ • _`.
While we need an auxiliary division semiring `R` to define `birkhoffAverage`,
the definition does not depend on the choice of `R`,
see `birkhoffAverage_congr_ring`.
-/
open Finset
section birkhoffAverage
variable (R : Type*) {α M : Type*} [DivisionSemiring R] [AddCommMonoid M] [Module R M]
/-- The average value of `g` on the first `n` points of the orbit of `x` under `f`,
i.e. the Birkhoff sum `∑ k ∈ Finset.range n, g (f^[k] x)` divided by `n`.
This average appears in many ergodic theorems
which say that `(birkhoffAverage R f g · x)`
converges to the "space average" `⨍ x, g x ∂μ` as `n → ∞`.
We use an auxiliary `[DivisionSemiring R]` to define division by `n`.
However, the definition does not depend on the choice of `R`,
see `birkhoffAverage_congr_ring`. -/
def birkhoffAverage (f : α → α) (g : α → M) (n : ℕ) (x : α) : M := (n : R)⁻¹ • birkhoffSum f g n x
theorem birkhoffAverage_zero (f : α → α) (g : α → M) (x : α) :
birkhoffAverage R f g 0 x = 0 := by simp [birkhoffAverage]
@[simp] theorem birkhoffAverage_zero' (f : α → α) (g : α → M) : birkhoffAverage R f g 0 = 0 :=
funext <| birkhoffAverage_zero _ _ _
theorem birkhoffAverage_one (f : α → α) (g : α → M) (x : α) :
birkhoffAverage R f g 1 x = g x := by simp [birkhoffAverage]
@[simp]
theorem birkhoffAverage_one' (f : α → α) (g : α → M) : birkhoffAverage R f g 1 = g :=
funext <| birkhoffAverage_one R f g
theorem map_birkhoffAverage (S : Type*) {F N : Type*}
[DivisionSemiring S] [AddCommMonoid N] [Module S N] [FunLike F M N]
[AddMonoidHomClass F M N] (g' : F) (f : α → α) (g : α → M) (n : ℕ) (x : α) :
g' (birkhoffAverage R f g n x) = birkhoffAverage S f (g' ∘ g) n x := by
simp only [birkhoffAverage, map_inv_natCast_smul g' R S, map_birkhoffSum]
theorem birkhoffAverage_congr_ring (S : Type*) [DivisionSemiring S] [Module S M]
(f : α → α) (g : α → M) (n : ℕ) (x : α) :
birkhoffAverage R f g n x = birkhoffAverage S f g n x :=
map_birkhoffAverage R S (AddMonoidHom.id M) f g n x
| Mathlib/Dynamics/BirkhoffSum/Average.lean | 68 | 70 | theorem birkhoffAverage_congr_ring' (S : Type*) [DivisionSemiring S] [Module S M] :
birkhoffAverage (α := α) (M := M) R = birkhoffAverage S := by | ext; apply birkhoffAverage_congr_ring |
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Johannes Hölzl, Yury Kudryashov, Patrick Massot
-/
import Mathlib.Algebra.GeomSum
import Mathlib.Order.Filter.AtTopBot.Archimedean
import Mathlib.Order.Iterate
import Mathlib.Topology.Algebra.Algebra
import Mathlib.Topology.Algebra.InfiniteSum.Real
import Mathlib.Topology.Instances.EReal.Lemmas
/-!
# A collection of specific limit computations
This file, by design, is independent of `NormedSpace` in the import hierarchy. It contains
important specific limit computations in metric spaces, in ordered rings/fields, and in specific
instances of these such as `ℝ`, `ℝ≥0` and `ℝ≥0∞`.
-/
assert_not_exists Basis NormedSpace
noncomputable section
open Set Function Filter Finset Metric Topology Nat uniformity NNReal ENNReal
variable {α : Type*} {β : Type*} {ι : Type*}
theorem tendsto_inverse_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ (n : ℝ)⁻¹) atTop (𝓝 0) :=
tendsto_inv_atTop_zero.comp tendsto_natCast_atTop_atTop
theorem tendsto_const_div_atTop_nhds_zero_nat (C : ℝ) :
Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := by
simpa only [mul_zero] using tendsto_const_nhds.mul tendsto_inverse_atTop_nhds_zero_nat
theorem tendsto_one_div_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ 1/(n : ℝ)) atTop (𝓝 0) :=
tendsto_const_div_atTop_nhds_zero_nat 1
theorem NNReal.tendsto_inverse_atTop_nhds_zero_nat :
Tendsto (fun n : ℕ ↦ (n : ℝ≥0)⁻¹) atTop (𝓝 0) := by
rw [← NNReal.tendsto_coe]
exact _root_.tendsto_inverse_atTop_nhds_zero_nat
theorem NNReal.tendsto_const_div_atTop_nhds_zero_nat (C : ℝ≥0) :
Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := by
simpa using tendsto_const_nhds.mul NNReal.tendsto_inverse_atTop_nhds_zero_nat
theorem EReal.tendsto_const_div_atTop_nhds_zero_nat {C : EReal} (h : C ≠ ⊥) (h' : C ≠ ⊤) :
Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := by
have : (fun n : ℕ ↦ C / n) = fun n : ℕ ↦ ((C.toReal / n : ℝ) : EReal) := by
ext n
nth_rw 1 [← coe_toReal h' h, ← coe_coe_eq_natCast n, ← coe_div C.toReal n]
rw [this, ← coe_zero, tendsto_coe]
exact _root_.tendsto_const_div_atTop_nhds_zero_nat C.toReal
theorem tendsto_one_div_add_atTop_nhds_zero_nat :
Tendsto (fun n : ℕ ↦ 1 / ((n : ℝ) + 1)) atTop (𝓝 0) :=
suffices Tendsto (fun n : ℕ ↦ 1 / (↑(n + 1) : ℝ)) atTop (𝓝 0) by simpa
(tendsto_add_atTop_iff_nat 1).2 (_root_.tendsto_const_div_atTop_nhds_zero_nat 1)
theorem NNReal.tendsto_algebraMap_inverse_atTop_nhds_zero_nat (𝕜 : Type*) [Semiring 𝕜]
[Algebra ℝ≥0 𝕜] [TopologicalSpace 𝕜] [ContinuousSMul ℝ≥0 𝕜] :
Tendsto (algebraMap ℝ≥0 𝕜 ∘ fun n : ℕ ↦ (n : ℝ≥0)⁻¹) atTop (𝓝 0) := by
convert (continuous_algebraMap ℝ≥0 𝕜).continuousAt.tendsto.comp
tendsto_inverse_atTop_nhds_zero_nat
rw [map_zero]
theorem tendsto_algebraMap_inverse_atTop_nhds_zero_nat (𝕜 : Type*) [Semiring 𝕜] [Algebra ℝ 𝕜]
[TopologicalSpace 𝕜] [ContinuousSMul ℝ 𝕜] :
Tendsto (algebraMap ℝ 𝕜 ∘ fun n : ℕ ↦ (n : ℝ)⁻¹) atTop (𝓝 0) :=
NNReal.tendsto_algebraMap_inverse_atTop_nhds_zero_nat 𝕜
/-- The limit of `n / (n + x)` is 1, for any constant `x` (valid in `ℝ` or any topological division
algebra over `ℝ`, e.g., `ℂ`).
TODO: introduce a typeclass saying that `1 / n` tends to 0 at top, making it possible to get this
statement simultaneously on `ℚ`, `ℝ` and `ℂ`. -/
theorem tendsto_natCast_div_add_atTop {𝕜 : Type*} [DivisionRing 𝕜] [TopologicalSpace 𝕜]
[CharZero 𝕜] [Algebra ℝ 𝕜] [ContinuousSMul ℝ 𝕜] [IsTopologicalDivisionRing 𝕜] (x : 𝕜) :
Tendsto (fun n : ℕ ↦ (n : 𝕜) / (n + x)) atTop (𝓝 1) := by
convert Tendsto.congr' ((eventually_ne_atTop 0).mp (Eventually.of_forall fun n hn ↦ _)) _
· exact fun n : ℕ ↦ 1 / (1 + x / n)
· field_simp [Nat.cast_ne_zero.mpr hn]
· have : 𝓝 (1 : 𝕜) = 𝓝 (1 / (1 + x * (0 : 𝕜))) := by
rw [mul_zero, add_zero, div_one]
rw [this]
refine tendsto_const_nhds.div (tendsto_const_nhds.add ?_) (by simp)
simp_rw [div_eq_mul_inv]
refine tendsto_const_nhds.mul ?_
have := ((continuous_algebraMap ℝ 𝕜).tendsto _).comp tendsto_inverse_atTop_nhds_zero_nat
rw [map_zero, Filter.tendsto_atTop'] at this
refine Iff.mpr tendsto_atTop' ?_
intros
simp_all only [comp_apply, map_inv₀, map_natCast]
/-- For any positive `m : ℕ`, `((n % m : ℕ) : ℝ) / (n : ℝ)` tends to `0` as `n` tends to `∞`. -/
| Mathlib/Analysis/SpecificLimits/Basic.lean | 97 | 113 | theorem tendsto_mod_div_atTop_nhds_zero_nat {m : ℕ} (hm : 0 < m) :
Tendsto (fun n : ℕ => ((n % m : ℕ) : ℝ) / (n : ℝ)) atTop (𝓝 0) := by | have h0 : ∀ᶠ n : ℕ in atTop, 0 ≤ (fun n : ℕ => ((n % m : ℕ) : ℝ)) n := by aesop
exact tendsto_bdd_div_atTop_nhds_zero h0
(.of_forall (fun n ↦ cast_le.mpr (mod_lt n hm).le)) tendsto_natCast_atTop_atTop
theorem Filter.EventuallyEq.div_mul_cancel {α G : Type*} [GroupWithZero G] {f g : α → G}
{l : Filter α} (hg : Tendsto g l (𝓟 {0}ᶜ)) : (fun x ↦ f x / g x * g x) =ᶠ[l] fun x ↦ f x := by
filter_upwards [hg.le_comap <| preimage_mem_comap (m := g) (mem_principal_self {0}ᶜ)] with x hx
aesop
/-- If `g` tends to `∞`, then eventually for all `x` we have `(f x / g x) * g x = f x`. -/
theorem Filter.EventuallyEq.div_mul_cancel_atTop {α K : Type*}
[Semifield K] [LinearOrder K] [IsStrictOrderedRing K]
{f g : α → K} {l : Filter α} (hg : Tendsto g l atTop) :
(fun x ↦ f x / g x * g x) =ᶠ[l] fun x ↦ f x :=
div_mul_cancel <| hg.mono_right <| le_principal_iff.mpr <| |
/-
Copyright (c) 2021 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.Algebra.Order.Ring.Rat
import Mathlib.Data.Multiset.Sort
import Mathlib.Data.PNat.Basic
import Mathlib.Data.PNat.Interval
import Mathlib.Tactic.NormNum
import Mathlib.Tactic.IntervalCases
/-!
# The inequality `p⁻¹ + q⁻¹ + r⁻¹ > 1`
In this file we classify solutions to the inequality
`(p⁻¹ + q⁻¹ + r⁻¹ : ℚ) > 1`, for positive natural numbers `p`, `q`, and `r`.
The solutions are exactly of the form.
* `A' q r := {1,q,r}`
* `D' r := {2,2,r}`
* `E6 := {2,3,3}`, or `E7 := {2,3,4}`, or `E8 := {2,3,5}`
This inequality shows up in Lie theory,
in the classification of Dynkin diagrams, root systems, and semisimple Lie algebras.
## Main declarations
* `pqr.A' q r`, the multiset `{1,q,r}`
* `pqr.D' r`, the multiset `{2,2,r}`
* `pqr.E6`, the multiset `{2,3,3}`
* `pqr.E7`, the multiset `{2,3,4}`
* `pqr.E8`, the multiset `{2,3,5}`
* `pqr.classification`, the classification of solutions to `p⁻¹ + q⁻¹ + r⁻¹ > 1`
-/
namespace ADEInequality
open Multiset
/-- `A' q r := {1,q,r}` is a `Multiset ℕ+`
that is a solution to the inequality
`(p⁻¹ + q⁻¹ + r⁻¹ : ℚ) > 1`. -/
def A' (q r : ℕ+) : Multiset ℕ+ :=
{1, q, r}
/-- `A r := {1,1,r}` is a `Multiset ℕ+`
that is a solution to the inequality
`(p⁻¹ + q⁻¹ + r⁻¹ : ℚ) > 1`.
These solutions are related to the Dynkin diagrams $A_r$. -/
def A (r : ℕ+) : Multiset ℕ+ :=
A' 1 r
/-- `D' r := {2,2,r}` is a `Multiset ℕ+`
that is a solution to the inequality
`(p⁻¹ + q⁻¹ + r⁻¹ : ℚ) > 1`.
These solutions are related to the Dynkin diagrams $D_{r+2}$. -/
def D' (r : ℕ+) : Multiset ℕ+ :=
{2, 2, r}
/-- `E' r := {2,3,r}` is a `Multiset ℕ+`.
For `r ∈ {3,4,5}` is a solution to the inequality
`(p⁻¹ + q⁻¹ + r⁻¹ : ℚ) > 1`.
These solutions are related to the Dynkin diagrams $E_{r+3}$. -/
def E' (r : ℕ+) : Multiset ℕ+ :=
{2, 3, r}
/-- `E6 := {2,3,3}` is a `Multiset ℕ+`
that is a solution to the inequality
`(p⁻¹ + q⁻¹ + r⁻¹ : ℚ) > 1`.
This solution is related to the Dynkin diagrams $E_6$. -/
def E6 : Multiset ℕ+ :=
E' 3
/-- `E7 := {2,3,4}` is a `Multiset ℕ+`
that is a solution to the inequality
`(p⁻¹ + q⁻¹ + r⁻¹ : ℚ) > 1`.
This solution is related to the Dynkin diagrams $E_7$. -/
def E7 : Multiset ℕ+ :=
E' 4
/-- `E8 := {2,3,5}` is a `Multiset ℕ+`
that is a solution to the inequality
`(p⁻¹ + q⁻¹ + r⁻¹ : ℚ) > 1`.
This solution is related to the Dynkin diagrams $E_8$. -/
def E8 : Multiset ℕ+ :=
E' 5
/-- `sum_inv pqr` for a `pqr : Multiset ℕ+` is the sum of the inverses
of the elements of `pqr`, as rational number.
The intended argument is a multiset `{p,q,r}` of cardinality `3`. -/
def sumInv (pqr : Multiset ℕ+) : ℚ :=
Multiset.sum (pqr.map fun (x : ℕ+) => x⁻¹)
theorem sumInv_pqr (p q r : ℕ+) : sumInv {p, q, r} = (p : ℚ)⁻¹ + (q : ℚ)⁻¹ + (r : ℚ)⁻¹ := by
simp only [sumInv, add_zero, insert_eq_cons, add_assoc, map_cons, sum_cons,
map_singleton, sum_singleton]
/-- A multiset `pqr` of positive natural numbers is `admissible`
if it is equal to `A' q r`, or `D' r`, or one of `E6`, `E7`, or `E8`. -/
def Admissible (pqr : Multiset ℕ+) : Prop :=
(∃ q r, A' q r = pqr) ∨ (∃ r, D' r = pqr) ∨ E' 3 = pqr ∨ E' 4 = pqr ∨ E' 5 = pqr
theorem admissible_A' (q r : ℕ+) : Admissible (A' q r) :=
Or.inl ⟨q, r, rfl⟩
theorem admissible_D' (n : ℕ+) : Admissible (D' n) :=
Or.inr <| Or.inl ⟨n, rfl⟩
theorem admissible_E'3 : Admissible (E' 3) :=
Or.inr <| Or.inr <| Or.inl rfl
theorem admissible_E'4 : Admissible (E' 4) :=
Or.inr <| Or.inr <| Or.inr <| Or.inl rfl
theorem admissible_E'5 : Admissible (E' 5) :=
Or.inr <| Or.inr <| Or.inr <| Or.inr rfl
theorem admissible_E6 : Admissible E6 :=
admissible_E'3
theorem admissible_E7 : Admissible E7 :=
admissible_E'4
theorem admissible_E8 : Admissible E8 :=
admissible_E'5
theorem Admissible.one_lt_sumInv {pqr : Multiset ℕ+} : Admissible pqr → 1 < sumInv pqr := by
rw [Admissible]
rintro (⟨p', q', H⟩ | ⟨n, H⟩ | H | H | H)
· rw [← H, A', sumInv_pqr, add_assoc]
simp only [lt_add_iff_pos_right, PNat.one_coe, inv_one, Nat.cast_one]
apply add_pos <;> simp only [PNat.pos, Nat.cast_pos, inv_pos]
· rw [← H, D', sumInv_pqr]
norm_num
all_goals
rw [← H, E', sumInv_pqr]
norm_num
theorem lt_three {p q r : ℕ+} (hpq : p ≤ q) (hqr : q ≤ r) (H : 1 < sumInv {p, q, r}) : p < 3 := by
have h3 : (0 : ℚ) < 3 := by norm_num
contrapose! H
rw [sumInv_pqr]
have h3q := H.trans hpq
have h3r := h3q.trans hqr
have hp : (p : ℚ)⁻¹ ≤ 3⁻¹ := by
rw [inv_le_inv₀ _ h3]
· assumption_mod_cast
· norm_num
have hq : (q : ℚ)⁻¹ ≤ 3⁻¹ := by
rw [inv_le_inv₀ _ h3]
· assumption_mod_cast
· norm_num
have hr : (r : ℚ)⁻¹ ≤ 3⁻¹ := by
rw [inv_le_inv₀ _ h3]
· assumption_mod_cast
· norm_num
calc
(p : ℚ)⁻¹ + (q : ℚ)⁻¹ + (r : ℚ)⁻¹ ≤ 3⁻¹ + 3⁻¹ + 3⁻¹ := add_le_add (add_le_add hp hq) hr
_ = 1 := by norm_num
theorem lt_four {q r : ℕ+} (hqr : q ≤ r) (H : 1 < sumInv {2, q, r}) : q < 4 := by
have h4 : (0 : ℚ) < 4 := by norm_num
contrapose! H
rw [sumInv_pqr]
have h4r := H.trans hqr
have hq : (q : ℚ)⁻¹ ≤ 4⁻¹ := by
rw [inv_le_inv₀ _ h4]
· assumption_mod_cast
· norm_num
have hr : (r : ℚ)⁻¹ ≤ 4⁻¹ := by
rw [inv_le_inv₀ _ h4]
· assumption_mod_cast
· norm_num
calc
(2⁻¹ + (q : ℚ)⁻¹ + (r : ℚ)⁻¹) ≤ 2⁻¹ + 4⁻¹ + 4⁻¹ := add_le_add (add_le_add le_rfl hq) hr
_ = 1 := by norm_num
theorem lt_six {r : ℕ+} (H : 1 < sumInv {2, 3, r}) : r < 6 := by
have h6 : (0 : ℚ) < 6 := by norm_num
contrapose! H
rw [sumInv_pqr]
have hr : (r : ℚ)⁻¹ ≤ 6⁻¹ := by
rw [inv_le_inv₀ _ h6]
· assumption_mod_cast
· norm_num
calc
(2⁻¹ + 3⁻¹ + (r : ℚ)⁻¹ : ℚ) ≤ 2⁻¹ + 3⁻¹ + 6⁻¹ := add_le_add (add_le_add le_rfl le_rfl) hr
_ = 1 := by norm_num
theorem admissible_of_one_lt_sumInv_aux' {p q r : ℕ+} (hpq : p ≤ q) (hqr : q ≤ r)
(H : 1 < sumInv {p, q, r}) : Admissible {p, q, r} := by
have hp3 : p < 3 := lt_three hpq hqr H
-- Porting note: `interval_cases` doesn't support `ℕ+` yet.
replace hp3 := Finset.mem_Iio.mpr hp3
conv at hp3 => change p ∈ ({1, 2} : Multiset ℕ+)
fin_cases hp3
· exact admissible_A' q r
have hq4 : q < 4 := lt_four hqr H
replace hq4 := Finset.mem_Ico.mpr ⟨hpq, hq4⟩; clear hpq
conv at hq4 => change q ∈ ({2, 3} : Multiset ℕ+)
fin_cases hq4
· exact admissible_D' r
have hr6 : r < 6 := lt_six H
replace hr6 := Finset.mem_Ico.mpr ⟨hqr, hr6⟩; clear hqr
conv at hr6 => change r ∈ ({3, 4, 5} : Multiset ℕ+)
fin_cases hr6
· exact admissible_E6
· exact admissible_E7
· exact admissible_E8
theorem admissible_of_one_lt_sumInv_aux :
∀ {pqr : List ℕ+} (_ : pqr.Sorted (· ≤ ·)) (_ : pqr.length = 3) (_ : 1 < sumInv pqr),
Admissible pqr
| [p, q, r], hs, _, H => by
obtain ⟨⟨hpq, -⟩, hqr⟩ : (p ≤ q ∧ p ≤ r) ∧ q ≤ r := by simpa using hs
exact admissible_of_one_lt_sumInv_aux' hpq hqr H
| Mathlib/NumberTheory/ADEInequality.lean | 229 | 248 | theorem admissible_of_one_lt_sumInv {p q r : ℕ+} (H : 1 < sumInv {p, q, r}) :
Admissible {p, q, r} := by | simp only [Admissible]
let S := sort ((· ≤ ·) : ℕ+ → ℕ+ → Prop) {p, q, r}
have hS : S.Sorted (· ≤ ·) := sort_sorted _ _
have hpqr : ({p, q, r} : Multiset ℕ+) = S := (sort_eq LE.le {p, q, r}).symm
rw [hpqr]
rw [hpqr] at H
apply admissible_of_one_lt_sumInv_aux hS _ H
simp only [S, insert_eq_cons, length_sort, card_cons, card_singleton]
/-- A multiset `{p,q,r}` of positive natural numbers
is a solution to `(p⁻¹ + q⁻¹ + r⁻¹ : ℚ) > 1` if and only if
it is `admissible` which means it is one of:
* `A' q r := {1,q,r}`
* `D' r := {2,2,r}`
* `E6 := {2,3,3}`, or `E7 := {2,3,4}`, or `E8 := {2,3,5}`
-/
theorem classification (p q r : ℕ+) : 1 < sumInv {p, q, r} ↔ Admissible {p, q, r} := |
/-
Copyright (c) 2022 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, Eric Wieser, Jeremy Avigad, Johan Commelin
-/
import Mathlib.Data.Matrix.Invertible
import Mathlib.LinearAlgebra.Matrix.NonsingularInverse
import Mathlib.LinearAlgebra.Matrix.PosDef
/-! # 2×2 block matrices and the Schur complement
This file proves properties of 2×2 block matrices `[A B; C D]` that relate to the Schur complement
`D - C*A⁻¹*B`.
Some of the results here generalize to 2×2 matrices in a category, rather than just a ring. A few
results in this direction can be found in the file `Mathlib.CategoryTheory.Preadditive.Biproducts`,
especially the declarations `CategoryTheory.Biprod.gaussian` and `CategoryTheory.Biprod.isoElim`.
Compare with `Matrix.invertibleOfFromBlocks₁₁Invertible`.
## Main results
* `Matrix.det_fromBlocks₁₁`, `Matrix.det_fromBlocks₂₂`: determinant of a block matrix in terms of
the Schur complement.
* `Matrix.invOf_fromBlocks_zero₂₁_eq`, `Matrix.invOf_fromBlocks_zero₁₂_eq`: the inverse of a
block triangular matrix.
* `Matrix.isUnit_fromBlocks_zero₂₁`, `Matrix.isUnit_fromBlocks_zero₁₂`: invertibility of a
block triangular matrix.
* `Matrix.det_one_add_mul_comm`: the **Weinstein–Aronszajn identity**.
* `Matrix.PosSemidef.fromBlocks₁₁` and `Matrix.PosSemidef.fromBlocks₂₂`: If a matrix `A` is
positive definite, then `[A B; Bᴴ D]` is positive semidefinite if and only if `D - Bᴴ A⁻¹ B` is
positive semidefinite.
-/
variable {l m n α : Type*}
namespace Matrix
open scoped Matrix
section CommRing
variable [Fintype l] [Fintype m] [Fintype n]
variable [DecidableEq l] [DecidableEq m] [DecidableEq n]
variable [CommRing α]
/-- LDU decomposition of a block matrix with an invertible top-left corner, using the
Schur complement. -/
theorem fromBlocks_eq_of_invertible₁₁ (A : Matrix m m α) (B : Matrix m n α) (C : Matrix l m α)
(D : Matrix l n α) [Invertible A] :
fromBlocks A B C D =
fromBlocks 1 0 (C * ⅟ A) 1 * fromBlocks A 0 0 (D - C * ⅟ A * B) *
fromBlocks 1 (⅟ A * B) 0 1 := by
simp only [fromBlocks_multiply, Matrix.mul_zero, Matrix.zero_mul, add_zero, zero_add,
Matrix.one_mul, Matrix.mul_one, invOf_mul_self, Matrix.mul_invOf_cancel_left,
Matrix.invOf_mul_cancel_right, Matrix.mul_assoc, add_sub_cancel]
/-- LDU decomposition of a block matrix with an invertible bottom-right corner, using the
Schur complement. -/
theorem fromBlocks_eq_of_invertible₂₂ (A : Matrix l m α) (B : Matrix l n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible D] :
fromBlocks A B C D =
fromBlocks 1 (B * ⅟ D) 0 1 * fromBlocks (A - B * ⅟ D * C) 0 0 D *
fromBlocks 1 0 (⅟ D * C) 1 :=
(Matrix.reindex (Equiv.sumComm _ _) (Equiv.sumComm _ _)).injective <| by
simpa [reindex_apply, Equiv.sumComm_symm, ← submatrix_mul_equiv _ _ _ (Equiv.sumComm n m), ←
submatrix_mul_equiv _ _ _ (Equiv.sumComm n l), Equiv.sumComm_apply,
fromBlocks_submatrix_sum_swap_sum_swap] using fromBlocks_eq_of_invertible₁₁ D C B A
section Triangular
/-! #### Block triangular matrices -/
/-- An upper-block-triangular matrix is invertible if its diagonal is. -/
def fromBlocksZero₂₁Invertible (A : Matrix m m α) (B : Matrix m n α) (D : Matrix n n α)
[Invertible A] [Invertible D] : Invertible (fromBlocks A B 0 D) :=
invertibleOfLeftInverse _ (fromBlocks (⅟ A) (-(⅟ A * B * ⅟ D)) 0 (⅟ D)) <| by
simp_rw [fromBlocks_multiply, Matrix.mul_zero, Matrix.zero_mul, zero_add, add_zero,
Matrix.neg_mul, invOf_mul_self, Matrix.invOf_mul_cancel_right, add_neg_cancel,
fromBlocks_one]
/-- A lower-block-triangular matrix is invertible if its diagonal is. -/
def fromBlocksZero₁₂Invertible (A : Matrix m m α) (C : Matrix n m α) (D : Matrix n n α)
[Invertible A] [Invertible D] : Invertible (fromBlocks A 0 C D) :=
invertibleOfLeftInverse _
(fromBlocks (⅟ A) 0 (-(⅟ D * C * ⅟ A))
(⅟ D)) <| by -- a symmetry argument is more work than just copying the proof
simp_rw [fromBlocks_multiply, Matrix.mul_zero, Matrix.zero_mul, zero_add, add_zero,
Matrix.neg_mul, invOf_mul_self, Matrix.invOf_mul_cancel_right, neg_add_cancel,
fromBlocks_one]
theorem invOf_fromBlocks_zero₂₁_eq (A : Matrix m m α) (B : Matrix m n α) (D : Matrix n n α)
[Invertible A] [Invertible D] [Invertible (fromBlocks A B 0 D)] :
⅟ (fromBlocks A B 0 D) = fromBlocks (⅟ A) (-(⅟ A * B * ⅟ D)) 0 (⅟ D) := by
letI := fromBlocksZero₂₁Invertible A B D
convert (rfl : ⅟ (fromBlocks A B 0 D) = _)
theorem invOf_fromBlocks_zero₁₂_eq (A : Matrix m m α) (C : Matrix n m α) (D : Matrix n n α)
[Invertible A] [Invertible D] [Invertible (fromBlocks A 0 C D)] :
⅟ (fromBlocks A 0 C D) = fromBlocks (⅟ A) 0 (-(⅟ D * C * ⅟ A)) (⅟ D) := by
letI := fromBlocksZero₁₂Invertible A C D
convert (rfl : ⅟ (fromBlocks A 0 C D) = _)
/-- Both diagonal entries of an invertible upper-block-triangular matrix are invertible (by reading
off the diagonal entries of the inverse). -/
def invertibleOfFromBlocksZero₂₁Invertible (A : Matrix m m α) (B : Matrix m n α) (D : Matrix n n α)
[Invertible (fromBlocks A B 0 D)] : Invertible A × Invertible D where
fst :=
invertibleOfLeftInverse _ (⅟ (fromBlocks A B 0 D)).toBlocks₁₁ <| by
have := invOf_mul_self (fromBlocks A B 0 D)
rw [← fromBlocks_toBlocks (⅟ (fromBlocks A B 0 D)), fromBlocks_multiply] at this
replace := congr_arg Matrix.toBlocks₁₁ this
simpa only [Matrix.toBlocks_fromBlocks₁₁, Matrix.mul_zero, add_zero, ← fromBlocks_one] using
this
snd :=
invertibleOfRightInverse _ (⅟ (fromBlocks A B 0 D)).toBlocks₂₂ <| by
have := mul_invOf_self (fromBlocks A B 0 D)
rw [← fromBlocks_toBlocks (⅟ (fromBlocks A B 0 D)), fromBlocks_multiply] at this
replace := congr_arg Matrix.toBlocks₂₂ this
simpa only [Matrix.toBlocks_fromBlocks₂₂, Matrix.zero_mul, zero_add, ← fromBlocks_one] using
this
/-- Both diagonal entries of an invertible lower-block-triangular matrix are invertible (by reading
off the diagonal entries of the inverse). -/
def invertibleOfFromBlocksZero₁₂Invertible (A : Matrix m m α) (C : Matrix n m α) (D : Matrix n n α)
[Invertible (fromBlocks A 0 C D)] : Invertible A × Invertible D where
fst :=
invertibleOfRightInverse _ (⅟ (fromBlocks A 0 C D)).toBlocks₁₁ <| by
have := mul_invOf_self (fromBlocks A 0 C D)
rw [← fromBlocks_toBlocks (⅟ (fromBlocks A 0 C D)), fromBlocks_multiply] at this
replace := congr_arg Matrix.toBlocks₁₁ this
simpa only [Matrix.toBlocks_fromBlocks₁₁, Matrix.zero_mul, add_zero, ← fromBlocks_one] using
this
snd :=
invertibleOfLeftInverse _ (⅟ (fromBlocks A 0 C D)).toBlocks₂₂ <| by
have := invOf_mul_self (fromBlocks A 0 C D)
rw [← fromBlocks_toBlocks (⅟ (fromBlocks A 0 C D)), fromBlocks_multiply] at this
replace := congr_arg Matrix.toBlocks₂₂ this
simpa only [Matrix.toBlocks_fromBlocks₂₂, Matrix.mul_zero, zero_add, ← fromBlocks_one] using
this
/-- `invertibleOfFromBlocksZero₂₁Invertible` and `Matrix.fromBlocksZero₂₁Invertible` form
an equivalence. -/
def fromBlocksZero₂₁InvertibleEquiv (A : Matrix m m α) (B : Matrix m n α) (D : Matrix n n α) :
Invertible (fromBlocks A B 0 D) ≃ Invertible A × Invertible D where
toFun _ := invertibleOfFromBlocksZero₂₁Invertible A B D
invFun i := by
letI := i.1
letI := i.2
exact fromBlocksZero₂₁Invertible A B D
left_inv _ := Subsingleton.elim _ _
right_inv _ := Subsingleton.elim _ _
/-- `invertibleOfFromBlocksZero₁₂Invertible` and `Matrix.fromBlocksZero₁₂Invertible` form
an equivalence. -/
def fromBlocksZero₁₂InvertibleEquiv (A : Matrix m m α) (C : Matrix n m α) (D : Matrix n n α) :
Invertible (fromBlocks A 0 C D) ≃ Invertible A × Invertible D where
toFun _ := invertibleOfFromBlocksZero₁₂Invertible A C D
invFun i := by
letI := i.1
letI := i.2
exact fromBlocksZero₁₂Invertible A C D
left_inv _ := Subsingleton.elim _ _
right_inv _ := Subsingleton.elim _ _
/-- An upper block-triangular matrix is invertible iff both elements of its diagonal are.
This is a propositional form of `Matrix.fromBlocksZero₂₁InvertibleEquiv`. -/
@[simp]
theorem isUnit_fromBlocks_zero₂₁ {A : Matrix m m α} {B : Matrix m n α} {D : Matrix n n α} :
IsUnit (fromBlocks A B 0 D) ↔ IsUnit A ∧ IsUnit D := by
simp only [← nonempty_invertible_iff_isUnit, ← nonempty_prod,
(fromBlocksZero₂₁InvertibleEquiv _ _ _).nonempty_congr]
/-- A lower block-triangular matrix is invertible iff both elements of its diagonal are.
This is a propositional form of `Matrix.fromBlocksZero₁₂InvertibleEquiv` forms an `iff`. -/
@[simp]
theorem isUnit_fromBlocks_zero₁₂ {A : Matrix m m α} {C : Matrix n m α} {D : Matrix n n α} :
IsUnit (fromBlocks A 0 C D) ↔ IsUnit A ∧ IsUnit D := by
simp only [← nonempty_invertible_iff_isUnit, ← nonempty_prod,
(fromBlocksZero₁₂InvertibleEquiv _ _ _).nonempty_congr]
/-- An expression for the inverse of an upper block-triangular matrix, when either both elements of
diagonal are invertible, or both are not. -/
theorem inv_fromBlocks_zero₂₁_of_isUnit_iff (A : Matrix m m α) (B : Matrix m n α) (D : Matrix n n α)
(hAD : IsUnit A ↔ IsUnit D) :
(fromBlocks A B 0 D)⁻¹ = fromBlocks A⁻¹ (-(A⁻¹ * B * D⁻¹)) 0 D⁻¹ := by
by_cases hA : IsUnit A
· have hD := hAD.mp hA
cases hA.nonempty_invertible
cases hD.nonempty_invertible
letI := fromBlocksZero₂₁Invertible A B D
simp_rw [← invOf_eq_nonsing_inv, invOf_fromBlocks_zero₂₁_eq]
· have hD := hAD.not.mp hA
have : ¬IsUnit (fromBlocks A B 0 D) :=
isUnit_fromBlocks_zero₂₁.not.mpr (not_and'.mpr fun _ => hA)
simp_rw [nonsing_inv_eq_ringInverse, Ring.inverse_non_unit _ hA, Ring.inverse_non_unit _ hD,
Ring.inverse_non_unit _ this, Matrix.zero_mul, neg_zero, fromBlocks_zero]
/-- An expression for the inverse of a lower block-triangular matrix, when either both elements of
diagonal are invertible, or both are not. -/
theorem inv_fromBlocks_zero₁₂_of_isUnit_iff (A : Matrix m m α) (C : Matrix n m α) (D : Matrix n n α)
(hAD : IsUnit A ↔ IsUnit D) :
(fromBlocks A 0 C D)⁻¹ = fromBlocks A⁻¹ 0 (-(D⁻¹ * C * A⁻¹)) D⁻¹ := by
by_cases hA : IsUnit A
· have hD := hAD.mp hA
cases hA.nonempty_invertible
cases hD.nonempty_invertible
letI := fromBlocksZero₁₂Invertible A C D
simp_rw [← invOf_eq_nonsing_inv, invOf_fromBlocks_zero₁₂_eq]
· have hD := hAD.not.mp hA
have : ¬IsUnit (fromBlocks A 0 C D) :=
isUnit_fromBlocks_zero₁₂.not.mpr (not_and'.mpr fun _ => hA)
simp_rw [nonsing_inv_eq_ringInverse, Ring.inverse_non_unit _ hA, Ring.inverse_non_unit _ hD,
Ring.inverse_non_unit _ this, Matrix.zero_mul, neg_zero, fromBlocks_zero]
end Triangular
/-! ### 2×2 block matrices -/
section Block
/-! #### General 2×2 block matrices -/
/-- A block matrix is invertible if the bottom right corner and the corresponding schur complement
is. -/
def fromBlocks₂₂Invertible (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible D] [Invertible (A - B * ⅟ D * C)] :
Invertible (fromBlocks A B C D) := by
-- factor `fromBlocks` via `fromBlocks_eq_of_invertible₂₂`, and state the inverse we expect
convert Invertible.copy' _ _ (fromBlocks (⅟ (A - B * ⅟ D * C)) (-(⅟ (A - B * ⅟ D * C) * B * ⅟ D))
(-(⅟ D * C * ⅟ (A - B * ⅟ D * C))) (⅟ D + ⅟ D * C * ⅟ (A - B * ⅟ D * C) * B * ⅟ D))
(fromBlocks_eq_of_invertible₂₂ _ _ _ _) _
· -- the product is invertible because all the factors are
letI : Invertible (1 : Matrix n n α) := invertibleOne
letI : Invertible (1 : Matrix m m α) := invertibleOne
refine Invertible.mul ?_ (fromBlocksZero₁₂Invertible _ _ _)
exact
Invertible.mul (fromBlocksZero₂₁Invertible _ _ _)
(fromBlocksZero₂₁Invertible _ _ _)
· -- unfold the `Invertible` instances to get the raw factors
show
_ =
fromBlocks 1 0 (-(1 * (⅟ D * C) * 1)) 1 *
(fromBlocks (⅟ (A - B * ⅟ D * C)) (-(⅟ (A - B * ⅟ D * C) * 0 * ⅟ D)) 0 (⅟ D) *
fromBlocks 1 (-(1 * (B * ⅟ D) * 1)) 0 1)
-- combine into a single block matrix
simp only [fromBlocks_multiply, invOf_one, Matrix.one_mul, Matrix.mul_one, Matrix.zero_mul,
Matrix.mul_zero, add_zero, zero_add, neg_zero, Matrix.mul_neg, Matrix.neg_mul, neg_neg, ←
Matrix.mul_assoc, add_comm (⅟D)]
/-- A block matrix is invertible if the top left corner and the corresponding schur complement
is. -/
def fromBlocks₁₁Invertible (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible A] [Invertible (D - C * ⅟ A * B)] :
Invertible (fromBlocks A B C D) := by
-- we argue by symmetry
letI := fromBlocks₂₂Invertible D C B A
letI iDCBA :=
submatrixEquivInvertible (fromBlocks D C B A) (Equiv.sumComm _ _) (Equiv.sumComm _ _)
exact
iDCBA.copy' _
(fromBlocks (⅟ A + ⅟ A * B * ⅟ (D - C * ⅟ A * B) * C * ⅟ A) (-(⅟ A * B * ⅟ (D - C * ⅟ A * B)))
(-(⅟ (D - C * ⅟ A * B) * C * ⅟ A)) (⅟ (D - C * ⅟ A * B)))
(fromBlocks_submatrix_sum_swap_sum_swap _ _ _ _).symm
(fromBlocks_submatrix_sum_swap_sum_swap _ _ _ _).symm
theorem invOf_fromBlocks₂₂_eq (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible D] [Invertible (A - B * ⅟ D * C)]
[Invertible (fromBlocks A B C D)] :
⅟ (fromBlocks A B C D) =
fromBlocks (⅟ (A - B * ⅟ D * C)) (-(⅟ (A - B * ⅟ D * C) * B * ⅟ D))
(-(⅟ D * C * ⅟ (A - B * ⅟ D * C))) (⅟ D + ⅟ D * C * ⅟ (A - B * ⅟ D * C) * B * ⅟ D) := by
letI := fromBlocks₂₂Invertible A B C D
convert (rfl : ⅟ (fromBlocks A B C D) = _)
theorem invOf_fromBlocks₁₁_eq (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible A] [Invertible (D - C * ⅟ A * B)]
[Invertible (fromBlocks A B C D)] :
⅟ (fromBlocks A B C D) =
fromBlocks (⅟ A + ⅟ A * B * ⅟ (D - C * ⅟ A * B) * C * ⅟ A) (-(⅟ A * B * ⅟ (D - C * ⅟ A * B)))
(-(⅟ (D - C * ⅟ A * B) * C * ⅟ A)) (⅟ (D - C * ⅟ A * B)) := by
letI := fromBlocks₁₁Invertible A B C D
convert (rfl : ⅟ (fromBlocks A B C D) = _)
/-- If a block matrix is invertible and so is its bottom left element, then so is the corresponding
Schur complement. -/
def invertibleOfFromBlocks₂₂Invertible (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible D] [Invertible (fromBlocks A B C D)] :
Invertible (A - B * ⅟ D * C) := by
suffices Invertible (fromBlocks (A - B * ⅟ D * C) 0 0 D) by
exact (invertibleOfFromBlocksZero₁₂Invertible (A - B * ⅟ D * C) 0 D).1
letI : Invertible (1 : Matrix n n α) := invertibleOne
letI : Invertible (1 : Matrix m m α) := invertibleOne
letI iDC : Invertible (fromBlocks 1 0 (⅟ D * C) 1 : Matrix (m ⊕ n) (m ⊕ n) α) :=
fromBlocksZero₁₂Invertible _ _ _
letI iBD : Invertible (fromBlocks 1 (B * ⅟ D) 0 1 : Matrix (m ⊕ n) (m ⊕ n) α) :=
fromBlocksZero₂₁Invertible _ _ _
letI iBDC := Invertible.copy ‹_› _ (fromBlocks_eq_of_invertible₂₂ A B C D).symm
refine (iBD.mulLeft _).symm ?_
exact (iDC.mulRight _).symm iBDC
/-- If a block matrix is invertible and so is its bottom left element, then so is the corresponding
Schur complement. -/
def invertibleOfFromBlocks₁₁Invertible (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible A] [Invertible (fromBlocks A B C D)] :
Invertible (D - C * ⅟ A * B) := by
-- another symmetry argument
letI iABCD' :=
submatrixEquivInvertible (fromBlocks A B C D) (Equiv.sumComm _ _) (Equiv.sumComm _ _)
letI iDCBA := iABCD'.copy _ (fromBlocks_submatrix_sum_swap_sum_swap _ _ _ _).symm
exact invertibleOfFromBlocks₂₂Invertible D C B A
/-- `Matrix.invertibleOfFromBlocks₂₂Invertible` and `Matrix.fromBlocks₂₂Invertible` as an
equivalence. -/
def invertibleEquivFromBlocks₂₂Invertible (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible D] :
Invertible (fromBlocks A B C D) ≃ Invertible (A - B * ⅟ D * C) where
toFun _iABCD := invertibleOfFromBlocks₂₂Invertible _ _ _ _
invFun _i_schur := fromBlocks₂₂Invertible _ _ _ _
left_inv _iABCD := Subsingleton.elim _ _
right_inv _i_schur := Subsingleton.elim _ _
/-- `Matrix.invertibleOfFromBlocks₁₁Invertible` and `Matrix.fromBlocks₁₁Invertible` as an
equivalence. -/
def invertibleEquivFromBlocks₁₁Invertible (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible A] :
Invertible (fromBlocks A B C D) ≃ Invertible (D - C * ⅟ A * B) where
toFun _iABCD := invertibleOfFromBlocks₁₁Invertible _ _ _ _
invFun _i_schur := fromBlocks₁₁Invertible _ _ _ _
left_inv _iABCD := Subsingleton.elim _ _
right_inv _i_schur := Subsingleton.elim _ _
/-- If the bottom-left element of a block matrix is invertible, then the whole matrix is invertible
iff the corresponding schur complement is. -/
theorem isUnit_fromBlocks_iff_of_invertible₂₂ {A : Matrix m m α} {B : Matrix m n α}
{C : Matrix n m α} {D : Matrix n n α} [Invertible D] :
IsUnit (fromBlocks A B C D) ↔ IsUnit (A - B * ⅟ D * C) := by
simp only [← nonempty_invertible_iff_isUnit,
(invertibleEquivFromBlocks₂₂Invertible A B C D).nonempty_congr]
/-- If the top-right element of a block matrix is invertible, then the whole matrix is invertible
iff the corresponding schur complement is. -/
theorem isUnit_fromBlocks_iff_of_invertible₁₁ {A : Matrix m m α} {B : Matrix m n α}
{C : Matrix n m α} {D : Matrix n n α} [Invertible A] :
IsUnit (fromBlocks A B C D) ↔ IsUnit (D - C * ⅟ A * B) := by
simp only [← nonempty_invertible_iff_isUnit,
(invertibleEquivFromBlocks₁₁Invertible A B C D).nonempty_congr]
end Block
/-! ### Lemmas about `Matrix.det` -/
section Det
/-- Determinant of a 2×2 block matrix, expanded around an invertible top left element in terms of
the Schur complement. -/
theorem det_fromBlocks₁₁ (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible A] :
(Matrix.fromBlocks A B C D).det = det A * det (D - C * ⅟ A * B) := by
rw [fromBlocks_eq_of_invertible₁₁ (A := A), det_mul, det_mul, det_fromBlocks_zero₂₁,
det_fromBlocks_zero₂₁, det_fromBlocks_zero₁₂, det_one, det_one, one_mul, one_mul, mul_one]
@[simp]
theorem det_fromBlocks_one₁₁ (B : Matrix m n α) (C : Matrix n m α) (D : Matrix n n α) :
(Matrix.fromBlocks 1 B C D).det = det (D - C * B) := by
haveI : Invertible (1 : Matrix m m α) := invertibleOne
rw [det_fromBlocks₁₁, invOf_one, Matrix.mul_one, det_one, one_mul]
/-- Determinant of a 2×2 block matrix, expanded around an invertible bottom right element in terms
of the Schur complement. -/
theorem det_fromBlocks₂₂ (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible D] :
(Matrix.fromBlocks A B C D).det = det D * det (A - B * ⅟ D * C) := by
have : fromBlocks A B C D =
(fromBlocks D C B A).submatrix (Equiv.sumComm _ _) (Equiv.sumComm _ _) := by
ext (i j)
cases i <;> cases j <;> rfl
rw [this, det_submatrix_equiv_self, det_fromBlocks₁₁]
@[simp]
theorem det_fromBlocks_one₂₂ (A : Matrix m m α) (B : Matrix m n α) (C : Matrix n m α) :
(Matrix.fromBlocks A B C 1).det = det (A - B * C) := by
haveI : Invertible (1 : Matrix n n α) := invertibleOne
rw [det_fromBlocks₂₂, invOf_one, Matrix.mul_one, det_one, one_mul]
/-- The **Weinstein–Aronszajn identity**. Note the `1` on the LHS is of shape m×m, while the `1` on
the RHS is of shape n×n. -/
theorem det_one_add_mul_comm (A : Matrix m n α) (B : Matrix n m α) :
det (1 + A * B) = det (1 + B * A) :=
calc
det (1 + A * B) = det (fromBlocks 1 (-A) B 1) := by
rw [det_fromBlocks_one₂₂, Matrix.neg_mul, sub_neg_eq_add]
_ = det (1 + B * A) := by rw [det_fromBlocks_one₁₁, Matrix.mul_neg, sub_neg_eq_add]
/-- Alternate statement of the **Weinstein–Aronszajn identity** -/
theorem det_mul_add_one_comm (A : Matrix m n α) (B : Matrix n m α) :
det (A * B + 1) = det (B * A + 1) := by rw [add_comm, det_one_add_mul_comm, add_comm]
| Mathlib/LinearAlgebra/Matrix/SchurComplement.lean | 406 | 413 | theorem det_one_sub_mul_comm (A : Matrix m n α) (B : Matrix n m α) :
det (1 - A * B) = det (1 - B * A) := by | rw [sub_eq_add_neg, ← Matrix.neg_mul, det_one_add_mul_comm, Matrix.mul_neg, ← sub_eq_add_neg]
/-- A special case of the **Matrix determinant lemma** for when `A = I`. -/
theorem det_one_add_replicateCol_mul_replicateRow {ι : Type*} [Unique ι] (u v : m → α) :
det (1 + replicateCol ι u * replicateRow ι v) = 1 + v ⬝ᵥ u := by
rw [det_one_add_mul_comm, det_unique, Pi.add_apply, Pi.add_apply, Matrix.one_apply_eq, |
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.AlgebraicGeometry.Cover.Open
import Mathlib.AlgebraicGeometry.GammaSpecAdjunction
import Mathlib.AlgebraicGeometry.Restrict
import Mathlib.CategoryTheory.Limits.Opposites
import Mathlib.RingTheory.Localization.InvSubmonoid
import Mathlib.RingTheory.RingHom.Surjective
import Mathlib.Topology.Sheaves.CommRingCat
/-!
# Affine schemes
We define the category of `AffineScheme`s as the essential image of `Spec`.
We also define predicates about affine schemes and affine open sets.
## Main definitions
* `AlgebraicGeometry.AffineScheme`: The category of affine schemes.
* `AlgebraicGeometry.IsAffine`: A scheme is affine if the canonical map `X ⟶ Spec Γ(X)` is an
isomorphism.
* `AlgebraicGeometry.Scheme.isoSpec`: The canonical isomorphism `X ≅ Spec Γ(X)` for an affine
scheme.
* `AlgebraicGeometry.AffineScheme.equivCommRingCat`: The equivalence of categories
`AffineScheme ≌ CommRingᵒᵖ` given by `AffineScheme.Spec : CommRingᵒᵖ ⥤ AffineScheme` and
`AffineScheme.Γ : AffineSchemeᵒᵖ ⥤ CommRingCat`.
* `AlgebraicGeometry.IsAffineOpen`: An open subset of a scheme is affine if the open subscheme is
affine.
* `AlgebraicGeometry.IsAffineOpen.fromSpec`: The immersion `Spec 𝒪ₓ(U) ⟶ X` for an affine `U`.
-/
-- Explicit universe annotations were used in this file to improve performance https://github.com/leanprover-community/mathlib4/issues/12737
noncomputable section
open CategoryTheory CategoryTheory.Limits Opposite TopologicalSpace
universe u
namespace AlgebraicGeometry
open Spec (structureSheaf)
/-- The category of affine schemes -/
def AffineScheme :=
Scheme.Spec.EssImageSubcategory
deriving Category
/-- A Scheme is affine if the canonical map `X ⟶ Spec Γ(X)` is an isomorphism. -/
class IsAffine (X : Scheme) : Prop where
affine : IsIso X.toSpecΓ
attribute [instance] IsAffine.affine
instance (X : Scheme.{u}) [IsAffine X] : IsIso (ΓSpec.adjunction.unit.app X) := @IsAffine.affine X _
/-- The canonical isomorphism `X ≅ Spec Γ(X)` for an affine scheme. -/
@[simps! -isSimp hom]
def Scheme.isoSpec (X : Scheme) [IsAffine X] : X ≅ Spec Γ(X, ⊤) :=
asIso X.toSpecΓ
@[reassoc]
theorem Scheme.isoSpec_hom_naturality {X Y : Scheme} [IsAffine X] [IsAffine Y] (f : X ⟶ Y) :
X.isoSpec.hom ≫ Spec.map (f.appTop) = f ≫ Y.isoSpec.hom := by
simp only [isoSpec, asIso_hom, Scheme.toSpecΓ_naturality]
@[reassoc]
theorem Scheme.isoSpec_inv_naturality {X Y : Scheme} [IsAffine X] [IsAffine Y] (f : X ⟶ Y) :
Spec.map (f.appTop) ≫ Y.isoSpec.inv = X.isoSpec.inv ≫ f := by
rw [Iso.eq_inv_comp, isoSpec, asIso_hom, ← Scheme.toSpecΓ_naturality_assoc, isoSpec,
asIso_inv, IsIso.hom_inv_id, Category.comp_id]
@[reassoc (attr := simp)]
lemma Scheme.toSpecΓ_isoSpec_inv (X : Scheme.{u}) [IsAffine X] :
X.toSpecΓ ≫ X.isoSpec.inv = 𝟙 _ :=
X.isoSpec.hom_inv_id
@[reassoc (attr := simp)]
lemma Scheme.isoSpec_inv_toSpecΓ (X : Scheme.{u}) [IsAffine X] :
X.isoSpec.inv ≫ X.toSpecΓ = 𝟙 _ :=
X.isoSpec.inv_hom_id
/-- Construct an affine scheme from a scheme and the information that it is affine.
Also see `AffineScheme.of` for a typeclass version. -/
@[simps]
def AffineScheme.mk (X : Scheme) (_ : IsAffine X) : AffineScheme :=
⟨X, ΓSpec.adjunction.mem_essImage_of_unit_isIso _⟩
/-- Construct an affine scheme from a scheme. Also see `AffineScheme.mk` for a non-typeclass
version. -/
def AffineScheme.of (X : Scheme) [h : IsAffine X] : AffineScheme :=
AffineScheme.mk X h
/-- Type check a morphism of schemes as a morphism in `AffineScheme`. -/
def AffineScheme.ofHom {X Y : Scheme} [IsAffine X] [IsAffine Y] (f : X ⟶ Y) :
AffineScheme.of X ⟶ AffineScheme.of Y :=
f
@[simp]
theorem essImage_Spec {X : Scheme} : Scheme.Spec.essImage X ↔ IsAffine X :=
⟨fun h => ⟨Functor.essImage.unit_isIso h⟩,
fun _ => ΓSpec.adjunction.mem_essImage_of_unit_isIso _⟩
@[deprecated (since := "2025-04-08")] alias mem_Spec_essImage := essImage_Spec
instance isAffine_affineScheme (X : AffineScheme.{u}) : IsAffine X.obj :=
⟨Functor.essImage.unit_isIso X.property⟩
instance (R : CommRingCatᵒᵖ) : IsAffine (Scheme.Spec.obj R) :=
AlgebraicGeometry.isAffine_affineScheme ⟨_, Scheme.Spec.obj_mem_essImage R⟩
instance isAffine_Spec (R : CommRingCat) : IsAffine (Spec R) :=
AlgebraicGeometry.isAffine_affineScheme ⟨_, Scheme.Spec.obj_mem_essImage (op R)⟩
theorem IsAffine.of_isIso {X Y : Scheme} (f : X ⟶ Y) [IsIso f] [h : IsAffine Y] : IsAffine X := by
rw [← essImage_Spec] at h ⊢; exact Functor.essImage.ofIso (asIso f).symm h
@[deprecated (since := "2025-03-31")] alias isAffine_of_isIso := IsAffine.of_isIso
/-- If `f : X ⟶ Y` is a morphism between affine schemes, the corresponding arrow is isomorphic
to the arrow of the morphism on prime spectra induced by the map on global sections. -/
noncomputable
def arrowIsoSpecΓOfIsAffine {X Y : Scheme} [IsAffine X] [IsAffine Y] (f : X ⟶ Y) :
Arrow.mk f ≅ Arrow.mk (Spec.map f.appTop) :=
Arrow.isoMk X.isoSpec Y.isoSpec (ΓSpec.adjunction.unit_naturality _)
/-- If `f : A ⟶ B` is a ring homomorphism, the corresponding arrow is isomorphic
to the arrow of the morphism induced on global sections by the map on prime spectra. -/
def arrowIsoΓSpecOfIsAffine {A B : CommRingCat} (f : A ⟶ B) :
Arrow.mk f ≅ Arrow.mk ((Spec.map f).appTop) :=
Arrow.isoMk (Scheme.ΓSpecIso _).symm (Scheme.ΓSpecIso _).symm
(Scheme.ΓSpecIso_inv_naturality f).symm
theorem Scheme.isoSpec_Spec (R : CommRingCat.{u}) :
(Spec R).isoSpec = Scheme.Spec.mapIso (Scheme.ΓSpecIso R).op :=
Iso.ext (SpecMap_ΓSpecIso_hom R).symm
@[simp] theorem Scheme.isoSpec_Spec_hom (R : CommRingCat.{u}) :
(Spec R).isoSpec.hom = Spec.map (Scheme.ΓSpecIso R).hom :=
(SpecMap_ΓSpecIso_hom R).symm
@[simp] theorem Scheme.isoSpec_Spec_inv (R : CommRingCat.{u}) :
(Spec R).isoSpec.inv = Spec.map (Scheme.ΓSpecIso R).inv :=
congr($(isoSpec_Spec R).inv)
lemma ext_of_isAffine {X Y : Scheme} [IsAffine Y] {f g : X ⟶ Y} (e : f.appTop = g.appTop) :
f = g := by
rw [← cancel_mono Y.toSpecΓ, Scheme.toSpecΓ_naturality, Scheme.toSpecΓ_naturality, e]
namespace AffineScheme
/-- The `Spec` functor into the category of affine schemes. -/
def Spec : CommRingCatᵒᵖ ⥤ AffineScheme :=
Scheme.Spec.toEssImage
/-! We copy over instances from `Scheme.Spec.toEssImage`. -/
instance Spec_full : Spec.Full := Functor.Full.toEssImage _
instance Spec_faithful : Spec.Faithful := Functor.Faithful.toEssImage _
instance Spec_essSurj : Spec.EssSurj := Functor.EssSurj.toEssImage (F := _)
/-- The forgetful functor `AffineScheme ⥤ Scheme`. -/
@[simps!]
def forgetToScheme : AffineScheme ⥤ Scheme :=
Scheme.Spec.essImage.ι
/-! We copy over instances from `Scheme.Spec.essImageInclusion`. -/
instance forgetToScheme_full : forgetToScheme.Full :=
inferInstanceAs Scheme.Spec.essImage.ι.Full
instance forgetToScheme_faithful : forgetToScheme.Faithful :=
inferInstanceAs Scheme.Spec.essImage.ι.Faithful
/-- The global section functor of an affine scheme. -/
def Γ : AffineSchemeᵒᵖ ⥤ CommRingCat :=
forgetToScheme.op ⋙ Scheme.Γ
/-- The category of affine schemes is equivalent to the category of commutative rings. -/
def equivCommRingCat : AffineScheme ≌ CommRingCatᵒᵖ :=
equivEssImageOfReflective.symm
instance : Γ.{u}.rightOp.IsEquivalence := equivCommRingCat.isEquivalence_functor
instance : Γ.{u}.rightOp.op.IsEquivalence := equivCommRingCat.op.isEquivalence_functor
instance ΓIsEquiv : Γ.{u}.IsEquivalence :=
inferInstanceAs (Γ.{u}.rightOp.op ⋙ (opOpEquivalence _).functor).IsEquivalence
instance hasColimits : HasColimits AffineScheme.{u} :=
haveI := Adjunction.has_limits_of_equivalence.{u} Γ.{u}
Adjunction.has_colimits_of_equivalence.{u} (opOpEquivalence AffineScheme.{u}).inverse
instance hasLimits : HasLimits AffineScheme.{u} := by
haveI := Adjunction.has_colimits_of_equivalence Γ.{u}
haveI : HasLimits AffineScheme.{u}ᵒᵖᵒᵖ := Limits.hasLimits_op_of_hasColimits
exact Adjunction.has_limits_of_equivalence (opOpEquivalence AffineScheme.{u}).inverse
noncomputable instance Γ_preservesLimits : PreservesLimits Γ.{u}.rightOp := inferInstance
noncomputable instance forgetToScheme_preservesLimits : PreservesLimits forgetToScheme := by
apply (config := { allowSynthFailures := true })
@preservesLimits_of_natIso _ _ _ _ _ _
(isoWhiskerRight equivCommRingCat.unitIso forgetToScheme).symm
change PreservesLimits (equivCommRingCat.functor ⋙ Scheme.Spec)
infer_instance
end AffineScheme
/-- An open subset of a scheme is affine if the open subscheme is affine. -/
def IsAffineOpen {X : Scheme} (U : X.Opens) : Prop :=
IsAffine U
/-- The set of affine opens as a subset of `opens X`. -/
def Scheme.affineOpens (X : Scheme) : Set X.Opens :=
{U : X.Opens | IsAffineOpen U}
instance {Y : Scheme.{u}} (U : Y.affineOpens) : IsAffine U :=
U.property
theorem isAffineOpen_opensRange {X Y : Scheme} [IsAffine X] (f : X ⟶ Y)
[H : IsOpenImmersion f] : IsAffineOpen (Scheme.Hom.opensRange f) := by
refine .of_isIso (IsOpenImmersion.isoOfRangeEq f (Y.ofRestrict _) ?_).inv
exact Subtype.range_val.symm
theorem isAffineOpen_top (X : Scheme) [IsAffine X] : IsAffineOpen (⊤ : X.Opens) := by
convert isAffineOpen_opensRange (𝟙 X)
ext1
exact Set.range_id.symm
instance Scheme.isAffine_affineCover (X : Scheme) (i : X.affineCover.J) :
IsAffine (X.affineCover.obj i) :=
isAffine_Spec _
instance Scheme.isAffine_affineBasisCover (X : Scheme) (i : X.affineBasisCover.J) :
IsAffine (X.affineBasisCover.obj i) :=
isAffine_Spec _
instance Scheme.isAffine_affineOpenCover (X : Scheme) (𝒰 : X.AffineOpenCover) (i : 𝒰.J) :
IsAffine (𝒰.openCover.obj i) :=
inferInstanceAs (IsAffine (Spec (𝒰.obj i)))
instance {X} [IsAffine X] (i) :
IsAffine ((Scheme.coverOfIsIso (P := @IsOpenImmersion) (𝟙 X)).obj i) := by
dsimp; infer_instance
theorem isBasis_affine_open (X : Scheme) : Opens.IsBasis X.affineOpens := by
rw [Opens.isBasis_iff_nbhd]
rintro U x (hU : x ∈ (U : Set X))
obtain ⟨S, hS, hxS, hSU⟩ := X.affineBasisCover_is_basis.exists_subset_of_mem_open hU U.isOpen
refine ⟨⟨S, X.affineBasisCover_is_basis.isOpen hS⟩, ?_, hxS, hSU⟩
rcases hS with ⟨i, rfl⟩
exact isAffineOpen_opensRange _
theorem iSup_affineOpens_eq_top (X : Scheme) : ⨆ i : X.affineOpens, (i : X.Opens) = ⊤ := by
apply Opens.ext
rw [Opens.coe_iSup]
apply IsTopologicalBasis.sUnion_eq
rw [← Set.image_eq_range]
exact isBasis_affine_open X
theorem Scheme.map_PrimeSpectrum_basicOpen_of_affine
(X : Scheme) [IsAffine X] (f : Γ(X, ⊤)) :
X.isoSpec.hom ⁻¹ᵁ PrimeSpectrum.basicOpen f = X.basicOpen f :=
Scheme.toSpecΓ_preimage_basicOpen _ _
theorem isBasis_basicOpen (X : Scheme) [IsAffine X] :
Opens.IsBasis (Set.range (X.basicOpen : Γ(X, ⊤) → X.Opens)) := by
delta Opens.IsBasis
convert PrimeSpectrum.isBasis_basic_opens.isInducing
(TopCat.homeoOfIso (Scheme.forgetToTop.mapIso X.isoSpec)).isInducing using 1
ext
simp only [Set.mem_image, exists_exists_eq_and]
constructor
· rintro ⟨_, ⟨x, rfl⟩, rfl⟩
refine ⟨_, ⟨_, ⟨x, rfl⟩, rfl⟩, ?_⟩
exact congr_arg Opens.carrier (Scheme.toSpecΓ_preimage_basicOpen _ _)
· rintro ⟨_, ⟨_, ⟨x, rfl⟩, rfl⟩, rfl⟩
refine ⟨_, ⟨x, rfl⟩, ?_⟩
exact congr_arg Opens.carrier (Scheme.toSpecΓ_preimage_basicOpen _ _).symm
/-- The canonical map `U ⟶ Spec Γ(X, U)` for an open `U ⊆ X`. -/
noncomputable
def Scheme.Opens.toSpecΓ {X : Scheme.{u}} (U : X.Opens) :
U.toScheme ⟶ Spec Γ(X, U) :=
U.toScheme.toSpecΓ ≫ Spec.map U.topIso.inv
@[reassoc (attr := simp)]
lemma Scheme.Opens.toSpecΓ_SpecMap_map {X : Scheme} (U V : X.Opens) (h : U ≤ V) :
U.toSpecΓ ≫ Spec.map (X.presheaf.map (homOfLE h).op) = X.homOfLE h ≫ V.toSpecΓ := by
delta Scheme.Opens.toSpecΓ
simp [← Spec.map_comp, ← X.presheaf.map_comp, toSpecΓ_naturality_assoc]
@[simp]
lemma Scheme.Opens.toSpecΓ_top {X : Scheme} :
(⊤ : X.Opens).toSpecΓ = (⊤ : X.Opens).ι ≫ X.toSpecΓ := by
simp [Scheme.Opens.toSpecΓ, toSpecΓ_naturality]; rfl
@[reassoc]
lemma Scheme.Opens.toSpecΓ_appTop {X : Scheme.{u}} (U : X.Opens) :
U.toSpecΓ.appTop = (Scheme.ΓSpecIso Γ(X, U)).hom ≫ U.topIso.inv := by
simp [Scheme.Opens.toSpecΓ]
namespace IsAffineOpen
variable {X Y : Scheme.{u}} {U : X.Opens} (hU : IsAffineOpen U) (f : Γ(X, U))
attribute [-simp] eqToHom_op in
/-- The isomorphism `U ≅ Spec Γ(X, U)` for an affine `U`. -/
@[simps! -isSimp inv]
def isoSpec :
↑U ≅ Spec Γ(X, U) :=
haveI : IsAffine U := hU
U.toScheme.isoSpec ≪≫ Scheme.Spec.mapIso U.topIso.symm.op
lemma isoSpec_hom : hU.isoSpec.hom = U.toSpecΓ := rfl
@[reassoc (attr := simp)]
lemma toSpecΓ_isoSpec_inv : U.toSpecΓ ≫ hU.isoSpec.inv = 𝟙 _ := hU.isoSpec.hom_inv_id
@[reassoc (attr := simp)]
lemma isoSpec_inv_toSpecΓ : hU.isoSpec.inv ≫ U.toSpecΓ = 𝟙 _ := hU.isoSpec.inv_hom_id
open IsLocalRing in
lemma isoSpec_hom_base_apply (x : U) :
hU.isoSpec.hom.base x = (Spec.map (X.presheaf.germ U x x.2)).base (closedPoint _) := by
dsimp [IsAffineOpen.isoSpec_hom, Scheme.isoSpec_hom, Scheme.toSpecΓ_base, Scheme.Opens.toSpecΓ]
rw [← Scheme.comp_base_apply, ← Spec.map_comp,
(Iso.eq_comp_inv _).mpr (Scheme.Opens.germ_stalkIso_hom U (V := ⊤) x trivial),
X.presheaf.germ_res_assoc, Spec.map_comp, Scheme.comp_base_apply]
congr 1
exact IsLocalRing.comap_closedPoint (U.stalkIso x).inv.hom
lemma isoSpec_inv_appTop :
hU.isoSpec.inv.appTop = U.topIso.hom ≫ (Scheme.ΓSpecIso Γ(X, U)).inv := by
simp_rw [Scheme.Opens.toScheme_presheaf_obj, isoSpec_inv, Scheme.isoSpec, asIso_inv,
Scheme.comp_app, Scheme.Opens.topIso_hom, Scheme.ΓSpecIso_inv_naturality,
Scheme.inv_appTop, -- `check_compositions` reports defeq problems starting after this step.
IsIso.inv_comp_eq]
rw [Scheme.toSpecΓ_appTop]
-- We need `erw` here because the goal has
-- `Scheme.ΓSpecIso Γ(↑U, ⊤)).hom ≫ Scheme.ΓSpecIso Γ(X, U.ι ''ᵁ ⊤)).inv`
-- and `Γ(X, U.ι ''ᵁ ⊤)` is non-reducibly defeq to `Γ(↑U, ⊤)`.
erw [Iso.hom_inv_id_assoc]
simp only [Opens.map_top]
lemma isoSpec_hom_appTop :
hU.isoSpec.hom.appTop = (Scheme.ΓSpecIso Γ(X, U)).hom ≫ U.topIso.inv := by
have := congr(inv $hU.isoSpec_inv_appTop)
rw [IsIso.inv_comp, IsIso.Iso.inv_inv, IsIso.Iso.inv_hom] at this
have := (Scheme.Γ.map_inv hU.isoSpec.inv.op).trans this
rwa [← op_inv, IsIso.Iso.inv_inv] at this
@[deprecated (since := "2024-11-16")] alias isoSpec_inv_app_top := isoSpec_inv_appTop
@[deprecated (since := "2024-11-16")] alias isoSpec_hom_app_top := isoSpec_hom_appTop
/-- The open immersion `Spec Γ(X, U) ⟶ X` for an affine `U`. -/
def fromSpec :
Spec Γ(X, U) ⟶ X :=
haveI : IsAffine U := hU
hU.isoSpec.inv ≫ U.ι
instance isOpenImmersion_fromSpec :
IsOpenImmersion hU.fromSpec := by
delta fromSpec
infer_instance
@[reassoc (attr := simp)]
lemma isoSpec_inv_ι : hU.isoSpec.inv ≫ U.ι = hU.fromSpec := rfl
@[reassoc (attr := simp)]
lemma toSpecΓ_fromSpec : U.toSpecΓ ≫ hU.fromSpec = U.ι := toSpecΓ_isoSpec_inv_assoc _ _
@[simp]
theorem range_fromSpec :
Set.range hU.fromSpec.base = (U : Set X) := by
delta IsAffineOpen.fromSpec; dsimp [IsAffineOpen.isoSpec_inv]
rw [Set.range_comp, Set.range_eq_univ.mpr, Set.image_univ]
· exact Subtype.range_coe
rw [← TopCat.coe_comp, ← TopCat.epi_iff_surjective]
infer_instance
@[simp]
theorem opensRange_fromSpec : hU.fromSpec.opensRange = U := Opens.ext (range_fromSpec hU)
@[reassoc (attr := simp)]
theorem map_fromSpec {V : X.Opens} (hV : IsAffineOpen V) (f : op U ⟶ op V) :
Spec.map (X.presheaf.map f) ≫ hU.fromSpec = hV.fromSpec := by
have : IsAffine U := hU
haveI : IsAffine _ := hV
conv_rhs =>
rw [fromSpec, ← X.homOfLE_ι (V := U) f.unop.le, isoSpec_inv, Category.assoc,
← Scheme.isoSpec_inv_naturality_assoc,
← Spec.map_comp_assoc, Scheme.homOfLE_appTop, ← Functor.map_comp]
rw [fromSpec, isoSpec_inv, Category.assoc, ← Spec.map_comp_assoc, ← Functor.map_comp]
rfl
@[reassoc]
lemma Spec_map_appLE_fromSpec (f : X ⟶ Y) {V : X.Opens} {U : Y.Opens}
(hU : IsAffineOpen U) (hV : IsAffineOpen V) (i : V ≤ f ⁻¹ᵁ U) :
Spec.map (f.appLE U V i) ≫ hU.fromSpec = hV.fromSpec ≫ f := by
have : IsAffine U := hU
simp only [IsAffineOpen.fromSpec, Category.assoc, isoSpec_inv]
simp_rw [← Scheme.homOfLE_ι _ i]
rw [Category.assoc, ← morphismRestrict_ι,
← Category.assoc _ (f ∣_ U) U.ι, ← @Scheme.isoSpec_inv_naturality_assoc,
← Spec.map_comp_assoc, ← Spec.map_comp_assoc, Scheme.comp_appTop, morphismRestrict_appTop,
Scheme.homOfLE_appTop, Scheme.Hom.app_eq_appLE, Scheme.Hom.appLE_map,
Scheme.Hom.appLE_map, Scheme.Hom.appLE_map, Scheme.Hom.map_appLE]
lemma fromSpec_top [IsAffine X] : (isAffineOpen_top X).fromSpec = X.isoSpec.inv := by
rw [fromSpec, isoSpec_inv, Category.assoc, ← @Scheme.isoSpec_inv_naturality,
← Spec.map_comp_assoc, Scheme.Opens.ι_appTop, ← X.presheaf.map_comp, ← op_comp,
eqToHom_comp_homOfLE, ← eqToHom_eq_homOfLE rfl, eqToHom_refl, op_id, X.presheaf.map_id,
Spec.map_id, Category.id_comp]
lemma fromSpec_app_of_le (V : X.Opens) (h : U ≤ V) :
hU.fromSpec.app V = X.presheaf.map (homOfLE h).op ≫
(Scheme.ΓSpecIso Γ(X, U)).inv ≫ (Spec _).presheaf.map (homOfLE le_top).op := by
have : U.ι ⁻¹ᵁ V = ⊤ := eq_top_iff.mpr fun x _ ↦ h x.2
rw [IsAffineOpen.fromSpec, Scheme.comp_app, Scheme.Opens.ι_app, Scheme.app_eq _ this,
← Scheme.Hom.appTop, IsAffineOpen.isoSpec_inv_appTop]
simp only [Scheme.Opens.toScheme_presheaf_map, Scheme.Opens.topIso_hom,
Category.assoc, ← X.presheaf.map_comp_assoc]
rfl
include hU in
protected theorem isCompact :
IsCompact (U : Set X) := by
convert @IsCompact.image _ _ _ _ Set.univ hU.fromSpec.base PrimeSpectrum.compactSpace.1
(by fun_prop)
convert hU.range_fromSpec.symm
exact Set.image_univ
include hU in
theorem image_of_isOpenImmersion (f : X ⟶ Y) [H : IsOpenImmersion f] :
IsAffineOpen (f ''ᵁ U) := by
have : IsAffine _ := hU
convert isAffineOpen_opensRange (U.ι ≫ f)
ext1
exact Set.image_eq_range _ _
theorem preimage_of_isIso {U : Y.Opens} (hU : IsAffineOpen U) (f : X ⟶ Y) [IsIso f] :
IsAffineOpen (f ⁻¹ᵁ U) :=
haveI : IsAffine _ := hU
.of_isIso (f ∣_ U)
theorem _root_.AlgebraicGeometry.Scheme.Hom.isAffineOpen_iff_of_isOpenImmersion
(f : AlgebraicGeometry.Scheme.Hom X Y) [H : IsOpenImmersion f] {U : X.Opens} :
IsAffineOpen (f ''ᵁ U) ↔ IsAffineOpen U where
mp hU := by
refine .of_isIso (IsOpenImmersion.isoOfRangeEq (X.ofRestrict U.isOpenEmbedding ≫ f)
(Y.ofRestrict _) ?_).hom (h := hU)
rw [Scheme.comp_base, TopCat.coe_comp, Set.range_comp]
dsimp [Opens.coe_inclusion', Scheme.restrict]
rw [Subtype.range_coe, Subtype.range_coe]
rfl
mpr hU := hU.image_of_isOpenImmersion f
/-- The affine open sets of an open subscheme corresponds to
the affine open sets containing in the image. -/
@[simps]
def _root_.AlgebraicGeometry.IsOpenImmersion.affineOpensEquiv (f : X ⟶ Y) [H : IsOpenImmersion f] :
X.affineOpens ≃ { U : Y.affineOpens // U ≤ f.opensRange } where
toFun U := ⟨⟨f ''ᵁ U, U.2.image_of_isOpenImmersion f⟩, Set.image_subset_range _ _⟩
invFun U := ⟨f ⁻¹ᵁ U, f.isAffineOpen_iff_of_isOpenImmersion.mp (by
rw [show f ''ᵁ f ⁻¹ᵁ U = U from Opens.ext (Set.image_preimage_eq_of_subset U.2)]; exact U.1.2)⟩
left_inv _ := Subtype.ext (Opens.ext (Set.preimage_image_eq _ H.base_open.injective))
right_inv U := Subtype.ext (Subtype.ext (Opens.ext (Set.image_preimage_eq_of_subset U.2)))
/-- The affine open sets of an open subscheme
corresponds to the affine open sets containing in the subset. -/
@[simps! apply_coe_coe]
def _root_.AlgebraicGeometry.affineOpensRestrict {X : Scheme.{u}} (U : X.Opens) :
U.toScheme.affineOpens ≃ { V : X.affineOpens // V ≤ U } :=
(IsOpenImmersion.affineOpensEquiv U.ι).trans (Equiv.subtypeEquivProp (by simp))
@[simp]
lemma _root_.AlgebraicGeometry.affineOpensRestrict_symm_apply_coe
{X : Scheme.{u}} (U : X.Opens) (V) :
((affineOpensRestrict U).symm V).1 = U.ι ⁻¹ᵁ V := rfl
instance (priority := 100) _root_.AlgebraicGeometry.Scheme.compactSpace_of_isAffine
(X : Scheme) [IsAffine X] :
CompactSpace X :=
⟨(isAffineOpen_top X).isCompact⟩
@[simp]
theorem fromSpec_preimage_self :
hU.fromSpec ⁻¹ᵁ U = ⊤ := by
ext1
rw [Opens.map_coe, Opens.coe_top, ← hU.range_fromSpec, ← Set.image_univ]
exact Set.preimage_image_eq _ PresheafedSpace.IsOpenImmersion.base_open.injective
theorem ΓSpecIso_hom_fromSpec_app :
(Scheme.ΓSpecIso Γ(X, U)).hom ≫ hU.fromSpec.app U =
(Spec Γ(X, U)).presheaf.map (eqToHom hU.fromSpec_preimage_self).op := by
simp only [fromSpec, Scheme.comp_coeBase, Opens.map_comp_obj, Scheme.comp_app,
Scheme.Opens.ι_app_self, eqToHom_op, Scheme.app_eq _ U.ι_preimage_self,
Scheme.Opens.toScheme_presheaf_map, eqToHom_unop, eqToHom_map U.ι.opensFunctor, Opens.map_top,
isoSpec_inv_appTop, Scheme.Opens.topIso_hom, Category.assoc, ← Functor.map_comp_assoc,
eqToHom_trans, eqToHom_refl, X.presheaf.map_id, Category.id_comp, Iso.hom_inv_id_assoc]
@[elementwise]
theorem fromSpec_app_self :
hU.fromSpec.app U = (Scheme.ΓSpecIso Γ(X, U)).inv ≫
(Spec Γ(X, U)).presheaf.map (eqToHom hU.fromSpec_preimage_self).op := by
rw [← hU.ΓSpecIso_hom_fromSpec_app, Iso.inv_hom_id_assoc]
theorem fromSpec_preimage_basicOpen' :
hU.fromSpec ⁻¹ᵁ X.basicOpen f = (Spec Γ(X, U)).basicOpen ((Scheme.ΓSpecIso Γ(X, U)).inv f) := by
rw [Scheme.preimage_basicOpen, hU.fromSpec_app_self]
exact Scheme.basicOpen_res_eq _ _ (eqToHom hU.fromSpec_preimage_self).op
theorem fromSpec_preimage_basicOpen :
hU.fromSpec ⁻¹ᵁ X.basicOpen f = PrimeSpectrum.basicOpen f := by
rw [fromSpec_preimage_basicOpen', ← basicOpen_eq_of_affine]
theorem fromSpec_image_basicOpen :
hU.fromSpec ''ᵁ (PrimeSpectrum.basicOpen f) = X.basicOpen f := by
rw [← hU.fromSpec_preimage_basicOpen]
ext1
change hU.fromSpec.base '' (hU.fromSpec.base ⁻¹' (X.basicOpen f : Set X)) = _
rw [Set.image_preimage_eq_inter_range, Set.inter_eq_left, hU.range_fromSpec]
exact Scheme.basicOpen_le _ _
@[simp]
theorem basicOpen_fromSpec_app :
(Spec Γ(X, U)).basicOpen (hU.fromSpec.app U f) = PrimeSpectrum.basicOpen f := by
rw [← hU.fromSpec_preimage_basicOpen, Scheme.preimage_basicOpen]
include hU in
| Mathlib/AlgebraicGeometry/AffineScheme.lean | 539 | 550 | theorem basicOpen :
IsAffineOpen (X.basicOpen f) := by | rw [← hU.fromSpec_image_basicOpen, Scheme.Hom.isAffineOpen_iff_of_isOpenImmersion]
convert isAffineOpen_opensRange
(Spec.map (CommRingCat.ofHom <| algebraMap Γ(X, U) (Localization.Away f)))
exact Opens.ext (PrimeSpectrum.localization_away_comap_range (Localization.Away f) f).symm
lemma Spec_basicOpen {R : CommRingCat} (f : R) :
IsAffineOpen (X := Spec R) (PrimeSpectrum.basicOpen f) :=
basicOpen_eq_of_affine f ▸ (isAffineOpen_top (Spec (.of R))).basicOpen _
instance [IsAffine X] (r : Γ(X, ⊤)) : IsAffine (X.basicOpen r) := |
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